Codebook

Norwegian Citizen Panel

Round 21

v-101 - 2023-11-22









Produced by ideas2evidence










Citation

Primary investigators

Name Affiliation
Elisabeth Ivarsflaten UiB
Stefan Dahlberg UiB
Erla Løvseth UiB
Hege Høivik Bye UiB
Lise Lund Bjånesøy UiB
Gisela Böhm UiB
Dag Elgesem UiB
Thea Gregersen UiB
Anne Lise Fimreite UiB
Arjan Hille Schakel UiB
Åsta Dyrnes Nordø NORCE
Erik Knudsen UiB
Soran Hajo Dahl UiB
Ingrid Kvåle Faleide UiB

Coordinating team

Name
Erla Løvseth
Ingrid Kvåle Faleide
Soran Hajo Dahl

Producers

Name Affiliation Role
Øivind Skjervheim ideas2evidence Coordinator
Olav Bjørnebekk ideas2evidence Project team member
Amund Eikrem ideas2evidence Project team member
Joachim Wettergreen ideas2evidence Project team member
Asle Høgestøl ideas2evidence Quality assurance

Study Description

Abstract

The Norwegian Citizen Panel is a platform for internet surveys of public opinion in important areas of society and politics in Norway. Participants are randomly recruited from the Norwegian population register, and they are encouraged to participate over time. The panel was fielded for the first time in the fall of 2013, and as of 2017 the survey is carried out three times a year. The University of Bergen owns and is responsible for the Citizen panel. The company ideas2evidence recruits respondents, produces the survey, and provides documentation of the data. Data is stored and shared by the Norwegian Social Science Data services (NSD). The Norwegian Citizen Panel welcomes research proposals for survey content. More information about calls and other updates are available at www.medborger.uib.no

Scope

Geographic coverage: National geographic coverage. Counties as geographic coding.
Unit of analysis: Individuals
Universe: Norwegian Citizens above the age of 18.

Methodology

Sampling procedure

Members of the Norwegian Citizen Panel have been recruited in seven waves:
In wave 1, 4 870 panel members were recruited (see documentation from wave 1).
In wave 3, 5 623 members were recruited (see documentation from wave 3).
In wave 8, 4 245 new members were recruited (see documentation from wave 8).
In wave 11, 2 069 panel members were recruited (see documentation from wave 11).
In wave 14, 2 036 panel members were recruited (see documentation from wave 14).
In wave 16, 5 163 panel members were recruited (see documentation from wave 16).
In wave 18, 2 048 panel members were recruited (see documentation from wave 18).

In wave 1 and 3 a gross sample of 25 000 individuals was randomly drawn from the Norwegian National Population Registry, while in wave 8 the gross sample amounted to 22 000 individuals. In wave 11, 14, and 18, a corresponding gross sample of 14 000 people was drawn. In wave 16, the gross sample was 34 000.

This National Population Registry includes everyone born in Norway as well as former and current inhabitants. The Norwegian Tax Administration is responsible for the register, but the administration is partly outsourced to the private IT-company Evry. Evry drew the sample on behalf of the Citizen Panel after the necessary permissions were acquired from the Norwegian Tax Administration.

The extracted data was a) last name, b) first name, c) address, d) gender, e) age, and f) phone number. The sample excluded people with no current home address in Norway.

Mode of Data Collection

The survey is based on a web-based questionnaire with postal recruitment. Please refer to documentation and other information from previous waves: https://nsd.no/nsddata/serier/norsk_medborgerpanel_eng.html

In wave 21, emails were sent out on 26th of May, 2021.

An e-mail with reminder was sent out three times, June 2nd, June 6th, and Juni 11th, respectively, to respondents who: a) had not logged in to the survey, or b) had not completed the survey. Panel members with registered mobile numbers received the last reminder via text message. Panel members without registered phone number were reminded by e-mail.

Wave 21 ended on June 15th 2021.

Weighting

To compensate for observed bias, a set of weights has been calculated. The weights equal the relation between a given strata in the population and the total population, divided by the relation between a given strata in the net sample and the total net sample. This procedure returns values around 1, but above 0. Respondents who are underrepresented will receive a weight above 1 and respondents who are overrepresented a weight below 1. The weights of the different strata are listed in the documentation report. When calculating the weights, the information regarding the respondent’s geographical location, gender and age are based on registry data. These attributes were included in the sample file we received from the Norwegian Population Register. Information regarding the level of education is provided by the respondents when answering the questionnaire.

Two different weights have been calculated:

When applied, both weights will provide a weighted N equal to the number of cases in the dataset. In other words, the weights are calculated using the whole dataset. NCP has an extensive use of (randomized) sub-groups, which might alter the demographic profile of the sub-group compared to the whole dataset. If custom weights are necessary, variable columns are included in the dataset that indicates the proportion size of strata in the population.

Note: In 2018 NCP changed the age variables in the datasets in order to make the respondents less identifiable. The weights are calculated with the old age variables, which no longer are publically available.


Change Log

Version Release date / Date changed Variable Changes and notes
v-101 2023-11-22 NA Revised release of round 21
NA 2023-10-25 r21Weight4 New variable: Added r21Weight4
NA 2023-10-25 r21Weight4 Variable documentation inserted
v-101 2023-10-25 NA Revised release of round 21
v-100 2021-07-01 NA Initial release of round 21


Dataset contents

File name Norwegian Citizen Panel - round 21 - v-101-O.sav
Distribution type Public
# Cases 10040
# Variables 324


Variable Documentation

responseid


Variable label: responseid
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21rekruttert


Variable label: [The wave the respondent was recruited]
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-18]

Value Label Cases Percentage
1 Round 1 1455 14.5% 0.14492032
3 Round 3 1581 15.7% 0.15747012
8 Round 8 1539 15.3% 0.15328685
11 Round 11 907 9.0% 0.09033865
14 Round 14 928 9.2% 0.09243028
16 Round 16 2538 25.3% 0.25278884
18 Round 18 1092 10.9% 0.10876494


r21group


Variable label: [Randomization of sub-groups]
Technical description: Randomized for all respondents
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Group 1 1989 19.8% 0.1981076
2 Group 2 2030 20.2% 0.2021912
3 Group 3 1941 19.3% 0.1933267
4 Group 4 2023 20.1% 0.2014940
5 Group 5 2057 20.5% 0.2048805


r21interview_start


Variable label: [Date and time of when the respondent first opened the questionnaire. Excel-format.]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21interview_end


Variable label: [Date and time of when the respondent completed the questionnaire. Excel-format.]
Technical attributes: [Question type: -] [Format:character] [Valid:9210] [Invalid:830] [Range:-]



r21browsertype


Variable label: [Browertype used by respondent]
Technical description: [Browertype used by respondent]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21browserversion


Variable label: [Browser version used by respondent]
Technical description: [Browser version used by respondent]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21mobil


Variable label: [Determines if the respondents uses mobile ]
Technical description: [Determines if the respondents uses mobile ]
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-1]

Value Label Cases Percentage
0 Other 5586 55.6% 0.5563745
1 Mobile 4454 44.4% 0.4436255


r21opplosning


Variable label: [Screen resolution of the applied device]
Technical description: [Screen resolution of the applied device]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21enhetstype


Variable label: [Determines respondents device type]
Technical description: [Determines respondents device type]
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 PC 5586 55.6% 0.556374502
2 Touch 4414 44.0% 0.439641434
3 Generic 40 0.4% 0.003984064


r21advancedwifeaturesenabled


Variable label: [Determine whether the respondent’s browser supports Advanced WI Features that require client side scripts, such as sliders, drag-n-drop ranking, images instead of radio-buttons/check-boxes etc.]
Technical description: [Determine whether the respondent’s browser supports Advanced WI Features that require client side scripts, such as sliders, drag-n-drop ranking, images instead of radio-buttons/check-boxes etc.]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21getrenderingmode


Variable label: [Detects the browsers rendering mode]
Technical description: [Detects the browsers rendering mode]
Technical attributes: [Question type: -] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21pk204


Variable label: Would vote for which party if parliamentary election tomorrow
Literal question: Which party would you vote for if there were a parliamentary election tomorrow?
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-13]

Value Label Cases Percentage
1 The Christian Democrats 273 2.7% 0.027191235
2 The Conservative Party 2167 21.6% 0.215836653
3 The Progress Party 662 6.6% 0.065936255
4 The Liberal Party 293 2.9% 0.029183267
5 The Socialist Left Party 964 9.6% 0.096015936
6 The Centre Party 1469 14.6% 0.146314741
7 The Green Party 523 5.2% 0.052091633
8 The Labour Party 2059 20.5% 0.205079681
9 The Red Party 581 5.8% 0.057868526
10 Would not vote 152 1.5% 0.015139442
11 Would cast a blank vote 223 2.2% 0.022211155
12 Not entitled to vote 218 2.2% 0.021713147
13 Other: 422 4.2% 0.042031873
97 Not answered 34 0.3% 0.003386454


r21pk204_13_other


Variable label: Other: Would vote for which party if parliamentary election tomorrow
Pre-question text: Which party would you vote for if there were a parliamentary election tomorrow?
Literal question: Other:
Technical description:

[All respondents asked]

[Answer list display order: Randomize]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Single - Other] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21tdr8a


Variable label: Would vote for which party if municipal elections tomorrow
Literal question: Which political party would you vote for if municipal elections were to take place tomorrow?
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-16]

Value Label Cases Percentage
1 The Christian Democrats 57 2.9% 0.028657617
2 The Conservative Party 452 22.7% 0.227249874
3 The Progress Party 104 5.2% 0.052287582
4 The Liberal Party 58 2.9% 0.029160382
5 The Socialist Left Party 156 7.8% 0.078431373
6 The Centre Party 243 12.2% 0.122171946
7 The Green Party 146 7.3% 0.073403720
8 The Labour Party 443 22.3% 0.222724987
9 The Red Party 123 6.2% 0.061840121
10 The People’s Movement - No to More Road Tolls (or similar road toll initiative) 11 0.6% 0.005530417
11 A joint party list 3 0.2% 0.001508296
12 A local list 33 1.7% 0.016591252
13 Would not vote 47 2.4% 0.023629965
14 Would cast a blank vote 30 1.5% 0.015082956
15 Not entitled to vote 2 0.1% 0.001005530
16 Other: 75 3.8% 0.037707391
97 Not answered 6 0.3% 0.003016591
98 Not asked 8051 NA


r21tdr8a_16_other


Variable label: Other: Would vote for which party if municipal elections tomorrow
Pre-question text: Which political party would you vote for if municipal elections were to take place tomorrow?
Literal question: Other:
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Single - Other] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21tdr8b


Variable label: Would vote for which party if county council elections tomorrow
Literal question: Which political party would you vote for if county council elections were to take place tomorrow?
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-16]

Value Label Cases Percentage
1 The Christian Democrats 55 2.8% 0.027652086
2 The Conservative Party 431 21.7% 0.216691805
3 The Progress Party 110 5.5% 0.055304173
4 The Liberal Party 58 2.9% 0.029160382
5 The Socialist Left Party 161 8.1% 0.080945199
6 The Centre Party 253 12.7% 0.127199598
7 The Green Party 140 7.0% 0.070387129
8 The Labour Party 393 19.8% 0.197586727
9 The Red Party 110 5.5% 0.055304173
10 The People’s Movement - No to More Road Tolls (or similar road toll initiative) 13 0.7% 0.006535948
11 A joint party list 0 0.0% 0.000000000
12 A local list 17 0.9% 0.008547009
13 Would not vote 59 3.0% 0.029663147
14 Would cast a blank vote 89 4.5% 0.044746104
15 Not entitled to vote 7 0.4% 0.003519356
16 Other: 78 3.9% 0.039215686
97 Not answered 15 0.8% 0.007541478
98 Not asked 8051 NA


r21tdr8b_16_other


Variable label: Other: Would vote for which party if county council elections tomorrow
Pre-question text: Which political party would you vote for if county council elections were to take place tomorrow?
Literal question: Other:
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Single - Other] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21pk6_1


Variable label: Like or dislike: The Christian Democrats
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Christian Democrats
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 1753 17.5% 0.174601594
2 Really dislike 2302 22.9% 0.229282869
3 Dislike somewhat 2474 24.6% 0.246414343
4 Neither dislike nor like 1734 17.3% 0.172709163
5 Like somewhat 1197 11.9% 0.119223108
6 Really like 369 3.7% 0.036752988
7 Intensely like 87 0.9% 0.008665339
97 Not answered 124 1.2% 0.012350598


r21pk6_2


Variable label: Like or dislike: The Conservative Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Conservative Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 628 6.3% 0.06254980
2 Really dislike 1495 14.9% 0.14890438
3 Dislike somewhat 2005 20.0% 0.19970120
4 Neither dislike nor like 1223 12.2% 0.12181275
5 Like somewhat 2204 22.0% 0.21952191
6 Really like 1844 18.4% 0.18366534
7 Intensely like 516 5.1% 0.05139442
97 Not answered 125 1.2% 0.01245020


r21pk6_3


Variable label: Like or dislike: The Progress Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Progress Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 3263 32.5% 0.32500000
2 Really dislike 2098 20.9% 0.20896414
3 Dislike somewhat 1506 15.0% 0.15000000
4 Neither dislike nor like 890 8.9% 0.08864542
5 Like somewhat 1267 12.6% 0.12619522
6 Really like 653 6.5% 0.06503984
7 Intensely like 240 2.4% 0.02390438
97 Not answered 123 1.2% 0.01225100


r21pk6_4


Variable label: Like or dislike: The Liberal Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Liberal Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 1043 10.4% 0.103884462
2 Really dislike 1622 16.2% 0.161553785
3 Dislike somewhat 2260 22.5% 0.225099602
4 Neither dislike nor like 2498 24.9% 0.248804781
5 Like somewhat 1872 18.6% 0.186454183
6 Really like 507 5.0% 0.050498008
7 Intensely like 78 0.8% 0.007768924
97 Not answered 160 1.6% 0.015936255


r21pk6_5


Variable label: Like or dislike: The Socialist Left Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Socialist Left Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 1269 12.6% 0.12639442
2 Really dislike 1612 16.1% 0.16055777
3 Dislike somewhat 1737 17.3% 0.17300797
4 Neither dislike nor like 1624 16.2% 0.16175299
5 Like somewhat 1878 18.7% 0.18705179
6 Really like 1364 13.6% 0.13585657
7 Intensely like 425 4.2% 0.04233068
97 Not answered 131 1.3% 0.01304781


r21pk6_6


Variable label: Like or dislike: The Centre Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Centre Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 542 5.4% 0.05398406
2 Really dislike 1074 10.7% 0.10697211
3 Dislike somewhat 1803 18.0% 0.17958167
4 Neither dislike nor like 2082 20.7% 0.20737052
5 Like somewhat 2563 25.5% 0.25527888
6 Really like 1472 14.7% 0.14661355
7 Intensely like 374 3.7% 0.03725100
97 Not answered 130 1.3% 0.01294821


r21pk6_7


Variable label: Like or dislike: The Green Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Green Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 2351 23.4% 0.23416335
2 Really dislike 1629 16.2% 0.16225100
3 Dislike somewhat 1604 16.0% 0.15976096
4 Neither dislike nor like 1285 12.8% 0.12798805
5 Like somewhat 1878 18.7% 0.18705179
6 Really like 927 9.2% 0.09233068
7 Intensely like 249 2.5% 0.02480080
97 Not answered 117 1.2% 0.01165339


r21pk6_8


Variable label: Like or dislike: The Labour Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Labour Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 363 3.6% 0.03615538
2 Really dislike 785 7.8% 0.07818725
3 Dislike somewhat 1796 17.9% 0.17888446
4 Neither dislike nor like 1599 15.9% 0.15926295
5 Like somewhat 2947 29.4% 0.29352590
6 Really like 2033 20.2% 0.20249004
7 Intensely like 389 3.9% 0.03874502
97 Not answered 128 1.3% 0.01274900


r21pk6_9


Variable label: Like or dislike: The Red Party
Pre-question text: We would like you to rate how much you like or dislike the various Norwegian political parties
Literal question: The Red Party
Technical description:

[All respondents asked]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Intensely dislike 2148 21.4% 0.21394422
2 Really dislike 1671 16.6% 0.16643426
3 Dislike somewhat 1481 14.8% 0.14750996
4 Neither dislike nor like 1573 15.7% 0.15667331
5 Like somewhat 1804 18.0% 0.17968127
6 Really like 875 8.7% 0.08715139
7 Intensely like 335 3.3% 0.03336653
97 Not answered 153 1.5% 0.01523904


r21meme1_1


Variable label: Identify as: Norwegian
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Norwegian
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme1_2


Variable label: Identify as: Sami
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Sami
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme1_3


Variable label: Identify as: Kven/Norwegian Finnish
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Kven/Norwegian Finnish
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme1_4


Variable label: Identify as: Forest Finn
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Forest Finn
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme1_5


Variable label: Identify as: Other
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Other
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme1_5_other


Variable label: Identify as: Other
Pre-question text: People have different ethnic origins. What do you identify as?
Literal question: Other
Post-question: You can tick multiple boxes.
Technical description:

[Asked if r21group = 4]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Multi - Other] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21meme2


Variable label: Open: What do you think of when you hear/read the word “Norwegianisation”?
Literal question: What do you think of when you hear or read the word “Norwegianisation”?
Post-question: You can be brief or write at length. We are looking for all types of answers.
Technical description:

[Asked if r21group = 4]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21meme3


Variable label: Aware that the Storting has appointed a commission to investigate the Norwegianisation policy?
Literal question: Are you aware that the Storting (the Norwegian parliament) has appointed a special truth and reconciliation commission to investigate the Norwegianisation policy that targeted Sami, Kven/Norwegian Finn, and Forest Finn people?
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Yes 552 27.3% 0.272862086
2 No 1462 72.3% 0.722689076
97 Not answered 9 0.4% 0.004448838
98 Not asked 8017 NA


r21meme4


Variable label: How important to survey the impact of the Norwegianisation policy on Sami/Kven language/culture?
Pre-question text: In 2018, the Storting appointed the Norwegian Truth and Reconciliation Commission to survey the impact of the Norwegianisation policy on Sami, Kven/Norwegian Finn, and Forest Finn people’s use and practice of their own language, culture, and traditional occupations.
Literal question: How important do you think such a commission is?
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 670 33.1% 0.331191300
2 Quite important 768 38.0% 0.379634207
3 Not very important 333 16.5% 0.164607019
4 Not important 107 5.3% 0.052891745
5 Don’t know 140 6.9% 0.069204152
97 Not answered 5 0.2% 0.002471577
98 Not asked 8017 NA


r21meme5


Variable label: To what extent a truth and reconciliation commission reconciles minority groups and the State
Literal question: To what extent do you think that a truth and reconciliation commission in Norway can contribute to reconciliation between minority groups (Sami, Kven/Norwegian Finn, and Forest Finn people) and the State?
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 To a very great extent 54 2.7% 0.026693030
2 To a great extent 322 15.9% 0.159169550
3 To some extent 1012 50.0% 0.500247158
4 To a small extent 333 16.5% 0.164607019
5 Not at all 94 4.6% 0.046465645
6 Don’t know 198 9.8% 0.097874444
97 Not answered 10 0.5% 0.004943154
98 Not asked 8017 NA


r21meme6


Variable label: To what extent a truth and reconciliation commission reconciles minority and majority groups
Literal question: To what extent do you believe truth and reconciliation commissions have an impact on reconciliation between different minority and majority groups?
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 To a very great extent 43 2.1% 0.021255561
2 To a great extent 282 13.9% 0.139396935
3 To some extent 1000 49.4% 0.494315373
4 To a small extent 396 19.6% 0.195748888
5 Not at all 98 4.8% 0.048442907
6 Don’t know 189 9.3% 0.093425606
97 Not answered 15 0.7% 0.007414731
98 Not asked 8017 NA


r21meme7_1


Variable label: Most people know about the Norwegianisation policy that targeted: Sami people
Pre-question text: How well do you think most people know about the State’s active Norwegianisation policy that targeted these groups and continued well into the second half of the 1900s?
Literal question: Sami people
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very well 130 6.4% 0.064260999
2 Well 594 29.4% 0.293623332
3 Not very well 900 44.5% 0.444883836
4 Not at all 194 9.6% 0.095897182
5 Don't know 194 9.6% 0.095897182
97 Not answered 11 0.5% 0.005437469
98 Not asked 8017 NA


r21meme7_2


Variable label: Most people know about the Norwegianisation policy that targeted: Kven/Norwegian Finns
Pre-question text: How well do you think most people know about the State’s active Norwegianisation policy that targeted these groups and continued well into the second half of the 1900s?
Literal question: Kven/Norwegian Finns
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very well 36 1.8% 0.01779535
2 Well 166 8.2% 0.08205635
3 Not very well 845 41.8% 0.41769649
4 Not at all 694 34.3% 0.34305487
5 Don't know 246 12.2% 0.12160158
97 Not answered 36 1.8% 0.01779535
98 Not asked 8017 NA


r21meme7_3


Variable label: Most people know about the Norwegianisation policy that targeted: Forest Finns
Pre-question text: How well do you think most people know about the State’s active Norwegianisation policy that targeted these groups and continued well into the second half of the 1900s?
Literal question: Forest Finns
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very well 30 1.5% 0.01482946
2 Well 106 5.2% 0.05239743
3 Not very well 732 36.2% 0.36183885
4 Not at all 857 42.4% 0.42362827
5 Don't know 263 13.0% 0.13000494
97 Not answered 35 1.7% 0.01730104
98 Not asked 8017 NA


r21meme8b_ran


Variable label: NA
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2056] [Invalid:7984] [Range:3-5]

Value Label Cases Percentage
3 construction of a new mosque 691 33.6% 0.3360895
4 that a centrally located chuch is conferted to a mosque 693 33.7% 0.3370623
5 that a centrally located existing building is converted to a mosque 672 32.7% 0.3268482
Sysmiss 7984 NA


r21meme8b


Variable label: In favour of/against permitting [r21meme8b_ran]?
Pre-question text: In some Norwegian municipalities there have been debates about permitting [r21meme8b_ran].
Literal question: Are you in favour of or against allowing this?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely in favour 269 13.1% 0.130772970
2 Somewhat in favour 598 29.1% 0.290714633
3 Somewhat against 502 24.4% 0.244044725
4 Completely against 673 32.7% 0.327175498
97 Not answered 15 0.7% 0.007292173
98 Not asked 7983 NA


r21meme11_ran1


Variable label: NA
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2056] [Invalid:7984] [Range:1-4]

Value Label Cases Percentage
1 [blank] 508 24.7% 0.2470817
2 because it is important that all women learn to swim 538 26.2% 0.2616732
3 because it makes women feel safer 528 25.7% 0.2568093
4 because this enables Muslim women to adhere to conservative rules in Islam 482 23.4% 0.2344358
Sysmiss 7984 NA


r21meme11


Variable label: Statment: Municipal swimming pools only open to women at certain times
Pre-question text: Some people think that municipal swimming pools should only be open to women at certain times [not mentioned/because it is important that all women learn to swim/because it makes women feel safer/because this enables Muslim women to adhere to conservative rules in Islam].
Literal question: Do you support or do you not support municipal swimming pools only being open to women at certain times?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely support 80 3.9% 0.038891590
2 Support 556 27.0% 0.270296548
3 Do not support 757 36.8% 0.368011667
4 Do not support at all 644 31.3% 0.313077297
97 Not answered 20 1.0% 0.009722897
98 Not asked 7983 NA


r21meme10_ran1


Variable label: NA
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2056] [Invalid:7984] [Range:1-3]

Value Label Cases Percentage
1 has been appointed to the council by the mayor 673 32.7% 0.3273346
2 has been elected to the council by the members of the largest Muslim organisation in the municipality 671 32.6% 0.3263619
3 has been appointed to the council by an imam (religious leader) from the largest mosque in the municipality 712 34.6% 0.3463035
Sysmiss 7984 NA


r21meme10_ran2


Variable label: NA
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2056] [Invalid:7984] [Range:1-2]

Value Label Cases Percentage
1 will represent the views of ordinary Muslims on the council 1031 50.1% 0.5014591
2 will contribute to improving the municipality’s decisions in such cases 1025 49.9% 0.4985409
Sysmiss 7984 NA


r21meme10


Variable label: Confident/doubt that Muslim representative in the municipality [represents Muslims/improves decisions]
Pre-question text: The leaders of a municipality want to appoint a council that will be consulted on issues where people with different backgrounds usually have different opinions, e.g. 17th May celebrations, 8th March commemorations, or Pride events. A Muslim representative [has been appointed to the council by the mayor/has been elected to the council by the members of the largest Muslim organisation in the municipality/has been appointed to the council by an imam (religious leader) from the largest mosque in the municipality].
Literal question: To what extent are you confident or do you doubt that the Muslim representative [will represent the views of ordinary Muslims on the council/will contribute to improving the municipality’s decisions in such cases]?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely confident 473 23.0% 0.22994652
2 Somewhat confident 892 43.4% 0.43364123
3 Doubt to some extent 468 22.8% 0.22751580
4 Doubt completely 202 9.8% 0.09820126
97 Not answered 22 1.1% 0.01069519
98 Not asked 7983 NA


r21kmopen1


Variable label: Open: What do you think when you hear or read the term “climate change”?
Literal question: What do you think when you hear or read the term “climate change”?
Post-question: Please write down the first thing you think of. All responses are welcome, preferably a couple of sentences, or just a few words if you would prefer.
Technical description:

[Asked if r21group = 4]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21kmopen2_ran


Variable label: Randomized text piping for r21kmopen2
Technical description: [Randomized if r21group = 1,3,4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5935] [Invalid:4105] [Range:1-3]

Value Label Cases Percentage
1 As far as climate change is concerned, what do you think should be done? 1904 32.1% 0.3208088
2 Norway has set ambitious targets for climate cuts in the coming years. What do you think could be obstacles to achieving the emissions targets? 2024 34.1% 0.3410278
3 Norway has set ambitious targets for climate cuts in the coming years. What do you think could be opportunities for achieving these emissions targets? 2007 33.8% 0.3381634
Sysmiss 4105 NA


r21kmopen2


Variable label: Open: [Obstacles/opportunities] for achieving emissions targets
Literal question: [As far as climate change is concerned, what do you think should be done?/Norway has set ambitious targets for climate cuts in the coming years. What do you think could be obstacles to achieving the emissions targets?/Norway has set ambitious targets for climate cuts in the coming years. What do you think could be opportunities for achieving these emissions targets?]
Post-question: Please write down the first thing you think of. All responses are welcome, preferably a couple of sentences, or just a few words if you would prefer.
Technical description:

[Asked if r21group = 1,3]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21tdr24


Variable label: Agree/disagree: Allocate more vaccine doses to areas that have had high infection rates over time
Pre-question text: There has been a debate in Norway about whether one should allocate more vaccine doses to areas with high infection rates over time. This means that municipalities with low infection rates would get fewer vaccine doses.
Literal question: To what extent do you agree or disagree that one should allocate more vaccine doses to areas that have had high infection rates over time?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 298 21.4% 0.213773314
2 Agree 409 29.3% 0.293400287
3 Agree somewhat 347 24.9% 0.248923960
4 Neither agree nor disagree 106 7.6% 0.076040172
5 Disagree somewhat 71 5.1% 0.050932568
6 Disagree 95 6.8% 0.068149211
7 Strongly disagree 62 4.4% 0.044476327
97 Not answered 6 0.4% 0.004304161
98 Not asked 8646 NA


r21tdr25_1


Variable label: How confident that: rural voters make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that rural voters make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 8 0.6% 0.005738881
1 1 7 0.5% 0.005021521
2 2 12 0.9% 0.008608321
3 3 48 3.4% 0.034433286
4 4 79 5.7% 0.056671449
5 5 221 15.9% 0.158536585
6 6 176 12.6% 0.126255380
7 7 264 18.9% 0.189383070
8 8 261 18.7% 0.187230990
9 9 98 7.0% 0.070301291
10 10 – Completely confident 206 14.8% 0.147776184
97 Not answered 14 1.0% 0.010043042
98 Not asked 8646 NA


r21tdr25_2


Variable label: How confident that: urban voters make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that urban voters make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 12 0.9% 0.008608321
1 1 9 0.6% 0.006456241
2 2 13 0.9% 0.009325681
3 3 48 3.4% 0.034433286
4 4 78 5.6% 0.055954089
5 5 299 21.4% 0.214490674
6 6 212 15.2% 0.152080344
7 7 261 18.7% 0.187230990
8 8 230 16.5% 0.164992826
9 9 69 4.9% 0.049497848
10 10 – Completely confident 149 10.7% 0.106886657
97 Not answered 14 1.0% 0.010043042
98 Not asked 8646 NA


r21tdr25_3


Variable label: How confident that: elected rural politicians make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that elected rural politicians make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 13 0.9% 0.009325681
1 1 7 0.5% 0.005021521
2 2 28 2.0% 0.020086083
3 3 58 4.2% 0.041606887
4 4 83 6.0% 0.059540890
5 5 268 19.2% 0.192252511
6 6 204 14.6% 0.146341463
7 7 274 19.7% 0.196556671
8 8 247 17.7% 0.177187948
9 9 88 6.3% 0.063127690
10 10 – Completely confident 111 8.0% 0.079626973
97 Not answered 13 0.9% 0.009325681
98 Not asked 8646 NA


r21tdr25_4


Variable label: How confident that: elected urban politicians make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that elected urban politicians make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 18 1.3% 0.012912482
1 1 11 0.8% 0.007890961
2 2 34 2.4% 0.024390244
3 3 65 4.7% 0.046628407
4 4 101 7.2% 0.072453372
5 5 297 21.3% 0.213055954
6 6 216 15.5% 0.154949785
7 7 264 18.9% 0.189383070
8 8 220 15.8% 0.157819225
9 9 66 4.7% 0.047345768
10 10 – Completely confident 88 6.3% 0.063127690
97 Not answered 14 1.0% 0.010043042
98 Not asked 8646 NA


r19identitet6_ran


Variable label: [Experiment. Randomly chooses an alternative for text piping in r19identitet6]
Technical description:

[Randomized if r19group = 3]

[Experiment. Randomly chooses an alternative for text piping in r19identitet6]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1391] [Invalid:8649] [Range:1-2]

Value Label Cases Percentage
1 in cities 696 50.0% 0.5003595
2 in villages 695 50.0% 0.4996405
Sysmiss 8649 NA


r19identitet6_ran_contra


Variable label: [Experiment. Opposite value of r19identitet6_ran]
Technical description:

[Randomized if r19group = 3]

[Experiment. Opposite value of r19identitet6_ran]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1391] [Invalid:8649] [Range:1-2]

Value Label Cases Percentage
1 in cities 695 50.0% 0.4996405
2 in villages 696 50.0% 0.5003595
Sysmiss 8649 NA


r21tdr26_1


Variable label: Agree/disagree: People [in cities/in villages] don’t appreciate life [in villages/in cities]
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in cities/in villages] don’t appreciate life [in villages/in cities].
Technical description: [Asked if r19group = 3 & r19identitet6_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 28 2.0% 0.02012940
2 Agree 150 10.8% 0.10783609
3 Agree somewhat 440 31.6% 0.31631919
4 Disagree somewhat 295 21.2% 0.21207764
5 Disagree 395 28.4% 0.28396837
6 Strongly disagree 62 4.5% 0.04457225
97 Not answered 21 1.5% 0.01509705
98 Not asked 8649 NA


r21tdr26_2


Variable label: Agree/disagree: People [in cities/in villages] get more than their fair share of public resources
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in cities/in villages] get more than their fair share of public resources.
Technical description: [Asked if r19group = 3 & r19identitet6_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 33 2.4% 0.02372394
2 Agree 152 10.9% 0.10927390
3 Agree somewhat 311 22.4% 0.22358016
4 Disagree somewhat 293 21.1% 0.21063983
5 Disagree 428 30.8% 0.30769231
6 Strongly disagree 151 10.9% 0.10855500
97 Not answered 23 1.7% 0.01653487
98 Not asked 8649 NA


r21tdr26_3


Variable label: Agree/disagree: People [in cities/in villages] think more about themselves than the nation as a whole
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in cities/in villages] think more about themselves than what is best for the nation as a whole.
Technical description: [Asked if r19group = 3 & r19identitet6_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 40 2.9% 0.02875629
2 Agree 156 11.2% 0.11214953
3 Agree somewhat 339 24.4% 0.24370956
4 Disagree somewhat 271 19.5% 0.19482387
5 Disagree 397 28.5% 0.28540618
6 Strongly disagree 167 12.0% 0.12005751
97 Not answered 21 1.5% 0.01509705
98 Not asked 8649 NA


r19identitet7_ran


Variable label: [Experiment. Randomly chooses an alternative for text piping in r19identitet7]
Technical description:

[Randomized if r19group = 3]

[Experiment. Randomly chooses an alternative for text piping in r19identitet7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1391] [Invalid:8649] [Range:1-2]

Value Label Cases Percentage
1 in Oslo 693 49.8% 0.4982027
2 outside Oslo 698 50.2% 0.5017973
Sysmiss 8649 NA


r19identitet7_ran_contra


Variable label: [Experiment. Opposite value of r19identitet7_ran]
Technical description:

[Randomized if r19group = 3]

[Experiment. Opposite value of r19identitet7_ran]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1391] [Invalid:8649] [Range:1-2]

Value Label Cases Percentage
1 in Oslo 698 50.2% 0.5017973
2 outside Oslo 693 49.8% 0.4982027
Sysmiss 8649 NA


r21tdr27_1


Variable label: Agree/disagree: People [in Oslo/outside Oslo] do not appreciate life [outside Oslo/in Oslo]
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in Oslo/outside Oslo] do not appreciate life [outside Oslo/in Oslo].
Technical description: [Asked if r19group = 3 & r19identitet7_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 45 3.2% 0.03235083
2 Agree 136 9.8% 0.09777139
3 Agree somewhat 468 33.6% 0.33644860
4 Disagree somewhat 328 23.6% 0.23580158
5 Disagree 339 24.4% 0.24370956
6 Strongly disagree 55 4.0% 0.03953990
97 Not answered 20 1.4% 0.01437815
98 Not asked 8649 NA


r21tdr27_2


Variable label: Agree/disagree: People [in Oslo/outside Oslo] get more than their fair share of public resources
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in Oslo/outside Oslo] get more than their fair share of public resources.
Technical description: [Asked if r19group = 3 & r19identitet7_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 51 3.7% 0.03666427
2 Agree 142 10.2% 0.10208483
3 Agree somewhat 280 20.1% 0.20129403
4 Disagree somewhat 345 24.8% 0.24802301
5 Disagree 410 29.5% 0.29475198
6 Strongly disagree 141 10.1% 0.10136592
97 Not answered 22 1.6% 0.01581596
98 Not asked 8649 NA


r21tdr27_3


Variable label: Agree/disagree: People [in Oslo/outside Oslo] think more about themselves than the nation as a whole
Pre-question text: To what extent do you agree or disagree with the following statements?
Literal question: People [in Oslo/outside Oslo] think more about themselves than what is best for the nation as a whole.
Technical description: [Asked if r19group = 3 & r19identitet7_ran is answered]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 57 4.1% 0.04097771
2 Agree 142 10.2% 0.10208483
3 Agree somewhat 363 26.1% 0.26096334
4 Disagree somewhat 296 21.3% 0.21279655
5 Disagree 374 26.9% 0.26887132
6 Strongly disagree 138 9.9% 0.09920920
97 Not answered 21 1.5% 0.01509705
98 Not asked 8649 NA


r21tdr28_1


Variable label: How confident that: voters from Oslo make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that voters from Oslo make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 37 2.7% 0.02654232
1 1 20 1.4% 0.01434720
2 2 32 2.3% 0.02295552
3 3 99 7.1% 0.07101865
4 4 127 9.1% 0.09110473
5 5 305 21.9% 0.21879484
6 6 191 13.7% 0.13701578
7 7 239 17.1% 0.17144907
8 8 186 13.3% 0.13342898
9 9 58 4.2% 0.04160689
10 10 – Completely confident 82 5.9% 0.05882353
97 Not answered 18 1.3% 0.01291248
98 Not asked 8646 NA


r21tdr28_2


Variable label: How confident that: voters from your region make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that voters from your region make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 10 0.7% 0.007173601
1 1 5 0.4% 0.003586801
2 2 12 0.9% 0.008608321
3 3 43 3.1% 0.030846485
4 4 83 6.0% 0.059540890
5 5 281 20.2% 0.201578192
6 6 232 16.6% 0.166427547
7 7 285 20.4% 0.204447633
8 8 241 17.3% 0.172883788
9 9 82 5.9% 0.058823529
10 10 – Completely confident 100 7.2% 0.071736011
97 Not answered 20 1.4% 0.014347202
98 Not asked 8646 NA


r21tdr28_3


Variable label: How confident that: elected politicians from Oslo make good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that elected politicians from Oslo make good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 38 2.7% 0.02725968
1 1 30 2.2% 0.02152080
2 2 51 3.7% 0.03658537
3 3 110 7.9% 0.07890961
4 4 124 8.9% 0.08895265
5 5 291 20.9% 0.20875179
6 6 188 13.5% 0.13486370
7 7 251 18.0% 0.18005739
8 8 183 13.1% 0.13127690
9 9 48 3.4% 0.03443329
10 10 – Completely confident 63 4.5% 0.04519369
97 Not answered 17 1.2% 0.01219512
98 Not asked 8646 NA


r21tdr28_4


Variable label: How confident that: elected politicians from your region good decisions
Pre-question text: On a scale of 0 to 10, how confident are you…
Literal question: that elected politicians from your region good decisions?
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-10]

Value Label Cases Percentage
0 0 – Not at all confident 14 1.0% 0.010043042
1 1 12 0.9% 0.008608321
2 2 22 1.6% 0.015781923
3 3 66 4.7% 0.047345768
4 4 96 6.9% 0.068866571
5 5 272 19.5% 0.195121951
6 6 219 15.7% 0.157101865
7 7 309 22.2% 0.221664275
8 8 222 15.9% 0.159253945
9 9 74 5.3% 0.053084648
10 10 – Completely confident 69 4.9% 0.049497848
97 Not answered 19 1.4% 0.013629842
98 Not asked 8646 NA


r21tdr29_1


Variable label: Agree/disagree: People in rural areas have too much say in Norwegian politics
Pre-question text: To what extent do you agree or disagree with the following statements:
Literal question: People in rural areas have too much say in Norwegian politics.
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 16 1.1% 0.01147776
2 Agree 78 5.6% 0.05595409
3 Agree somewhat 210 15.1% 0.15064562
4 Disagree somewhat 347 24.9% 0.24892396
5 Disagree 547 39.2% 0.39239598
6 Strongly disagree 177 12.7% 0.12697274
97 Not answered 19 1.4% 0.01362984
98 Not asked 8646 NA


r21tdr29_2


Variable label: Agree/disagree: People in urban areas have too much say in Norwegian politics
Pre-question text: To what extent do you agree or disagree with the following statements:
Literal question: People in urban areas have too much say in Norwegian politics.
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 46 3.3% 0.03299857
2 Agree 162 11.6% 0.11621234
3 Agree somewhat 363 26.0% 0.26040172
4 Disagree somewhat 397 28.5% 0.28479197
5 Disagree 342 24.5% 0.24533716
6 Strongly disagree 62 4.4% 0.04447633
97 Not answered 22 1.6% 0.01578192
98 Not asked 8646 NA


r21tdr30_1


Variable label: Agree/disagree: People in Oslo have too much say in Norwegian politics
Pre-question text: To what extent do you agree or disagree with the following statements:
Literal question: People in Oslo have too much say in Norwegian politics.
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 90 6.5% 0.06456241
2 Agree 209 15.0% 0.14992826
3 Agree somewhat 438 31.4% 0.31420373
4 Disagree somewhat 307 22.0% 0.22022956
5 Disagree 267 19.2% 0.19153515
6 Strongly disagree 47 3.4% 0.03371593
97 Not answered 36 2.6% 0.02582496
98 Not asked 8646 NA


r21tdr30_2


Variable label: Agree/disagree: People outside Oslo have too much say in Norwegian politics
Pre-question text: To what extent do you agree or disagree with the following statements:
Literal question: People outside Oslo have too much say in Norwegian politics.
Technical description: [Asked if r19group = 3]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Strongly agree 16 1.1% 0.01147776
2 Agree 42 3.0% 0.03012912
3 Agree somewhat 198 14.2% 0.14203730
4 Disagree somewhat 551 39.5% 0.39526542
5 Disagree 461 33.1% 0.33070301
6 Strongly disagree 92 6.6% 0.06599713
97 Not answered 34 2.4% 0.02439024
98 Not asked 8646 NA


r21_psykpr1


Variable label: How high do you consider the risk to become infected by the coronavirus?
Literal question: How high do you consider the risk that during the outbreak you will become infected by the coronavirus?
Technical description: [Asked if r20group = 6]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very low 751 38.0% 0.3802531646
2 Somewhat low 667 33.8% 0.3377215190
3 Medium 432 21.9% 0.2187341772
4 Somewhat high 97 4.9% 0.0491139241
5 Very high 27 1.4% 0.0136708861
97 Not answered 1 0.1% 0.0005063291
98 Not asked 8065 NA


r21_covid_plager_1


Variable label: Experienced to feel, during the Covid-19 pandemic: Scared/anxious
Pre-question text: Below you will find a list of various ailments. To what extent have you experienced any of this during the Covid-19 pandemic?
Literal question: Feeling scared or anxious
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21_covid_plager_2


Variable label: Experienced to feel, during the Covid-19 pandemic: Nervous, inner turmoil
Pre-question text: Below you will find a list of various ailments. To what extent have you experienced any of this during the Covid-19 pandemic?
Literal question: Nervous, inner turmoil
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21_covid_plager_3


Variable label: Experienced to feel, during the Covid-19 pandemic: Depressed, low (sad)
Pre-question text: Below you will find a list of various ailments. To what extent have you experienced any of this during the Covid-19 pandemic?
Literal question: Feeling depressed, low (sad)
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21_covid_plager_4


Variable label: Experienced to feel, during the Covid-19 pandemic: Worrying too much
Pre-question text: Below you will find a list of various ailments. To what extent have you experienced any of this during the Covid-19 pandemic?
Literal question: Worrying too much
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21_covid_plager_5


Variable label: Experienced to feel, during the Covid-19 pandemic: Hopelessness about the future
Pre-question text: Below you will find a list of various ailments. To what extent have you experienced any of this during the Covid-19 pandemic?
Literal question: Feelings of hopelessness about the future
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid1


Variable label: Are you or have you been infected with the coronavirus?
Literal question: Are you or have you been infected with the coronavirus?
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid2


Variable label: Have you been unsure if you may be infected with the coronavirus?
Literal question: Have you at any point been unsure if you may be infected with the coronavirus?
Technical description:

[Asked if r21covid1 = 3 & r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid3


Variable label: Have you been tested for possible Covid-19 infection or contacted a doctor due to suspicion?
Literal question: Have you been tested for possible Covid-19 infection or contacted a doctor because you suspected you might be infected?
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid3_1_other


Variable label: How many times: Tested for/contacted doctor due to possible Covid-19 infection?
Pre-question text: Have you been tested for possible Covid-19 infection or contacted a doctor because you suspected you might be infected?
Literal question: times
Technical description:

[Asked if r20group = 6]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Single - Other] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid4_1


Variable label: Have you during the pandemic been in: Isolation
Pre-question text:

Have you been in quarantine or isolation during the pandemic?

Explanation of the different terms:

Isolation means staying at home or another appropriate place all of the time and not going out, with the exception of your own garden or a private outside area, that you must stay at home at all times (or another appropriate place) and are only allowed to be in your own garden or outside area.

Quarantine means staying at home or another appropriate place and avoiding anywhere you cannot maintain your distance from others, that you must stay at home (or another appropriate place) and must avoid anywhere you cannot maintain your distance from others.

Temporary quarantine is a temporary period where you stay at home while waiting for the test results of a close contact who has possibly been infected, when you must stay at home while waiting for the test results of a close contact who may possibly have been infected.
Literal question: Isolation (imposed by the health authorities)
Post-question: Tick all that are relevant.
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid4_2


Variable label: Have you during the pandemic been in: Voluntary isolation
Pre-question text:

Have you been in quarantine or isolation during the pandemic?

Explanation of the different terms:

Isolation means staying at home or another appropriate place all of the time and not going out, with the exception of your own garden or a private outside area, that you must stay at home at all times (or another appropriate place) and are only allowed to be in your own garden or outside area.

Quarantine means staying at home or another appropriate place and avoiding anywhere you cannot maintain your distance from others, that you must stay at home (or another appropriate place) and must avoid anywhere you cannot maintain your distance from others.

Temporary quarantine is a temporary period where you stay at home while waiting for the test results of a close contact who has possibly been infected, when you must stay at home while waiting for the test results of a close contact who may possibly have been infected.
Literal question: Voluntary isolation
Post-question: Tick all that are relevant.
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid4_3


Variable label: Have you during the pandemic been in: Quarantine/temporary quarantine
Pre-question text:

Have you been in quarantine or isolation during the pandemic?

Explanation of the different terms:

Isolation means staying at home or another appropriate place all of the time and not going out, with the exception of your own garden or a private outside area, that you must stay at home at all times (or another appropriate place) and are only allowed to be in your own garden or outside area.

Quarantine means staying at home or another appropriate place and avoiding anywhere you cannot maintain your distance from others, that you must stay at home (or another appropriate place) and must avoid anywhere you cannot maintain your distance from others.

Temporary quarantine is a temporary period where you stay at home while waiting for the test results of a close contact who has possibly been infected, when you must stay at home while waiting for the test results of a close contact who may possibly have been infected.
Literal question: Quarantine or temporary quarantine (imposed by the health authorities)
Post-question: Tick all that are relevant.
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid4_4


Variable label: Have you during the pandemic been in: Voluntary/temporary quarantine
Pre-question text:

Have you been in quarantine or isolation during the pandemic?

Explanation of the different terms:

Isolation means staying at home or another appropriate place all of the time and not going out, with the exception of your own garden or a private outside area, that you must stay at home at all times (or another appropriate place) and are only allowed to be in your own garden or outside area.

Quarantine means staying at home or another appropriate place and avoiding anywhere you cannot maintain your distance from others, that you must stay at home (or another appropriate place) and must avoid anywhere you cannot maintain your distance from others.

Temporary quarantine is a temporary period where you stay at home while waiting for the test results of a close contact who has possibly been infected, when you must stay at home while waiting for the test results of a close contact who may possibly have been infected.
Literal question: Voluntary quarantine or temporary quarantine
Post-question: Tick all that are relevant.
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21covid4_5


Variable label: Have you during the pandemic been in: quarantine/isolation
Pre-question text:

Have you been in quarantine or isolation during the pandemic?

Explanation of the different terms:

Isolation means staying at home or another appropriate place all of the time and not going out, with the exception of your own garden or a private outside area, that you must stay at home at all times (or another appropriate place) and are only allowed to be in your own garden or outside area.

Quarantine means staying at home or another appropriate place and avoiding anywhere you cannot maintain your distance from others, that you must stay at home (or another appropriate place) and must avoid anywhere you cannot maintain your distance from others.

Temporary quarantine is a temporary period where you stay at home while waiting for the test results of a close contact who has possibly been infected, when you must stay at home while waiting for the test results of a close contact who may possibly have been infected.
Literal question: No, I have not been in quarantine or isolation
Post-question: Tick all that are relevant.
Technical description:

[Asked if r20group = 6]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21cov_psykac1


Variable label: Agree/disagree: Do my best to follow the health authorities’ advice to limit the risk of infection
Pre-question text:

To what extent do you agree or disagree with the following statement:

Literal question: I do my best to follow the health authorities’ advice to limit the risk of infection (wash my hands frequently, avoid travel and situations involving contact with other people, keep distance and avoid touching things).
Technical description: [Asked if r20group = 6]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely disagree 71 3.6% 0.035949367
2 Disagree 10 0.5% 0.005063291
3 Neither agree nor disagree 40 2.0% 0.020253165
4 Agree 623 31.5% 0.315443038
5 Completely agree 1229 62.2% 0.622278481
97 Not answered 2 0.1% 0.001012658
98 Not asked 8065 NA


r21meme_skatt1_ran1


Variable label: NA
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5132] [Invalid:4908] [Range:1-5]

Value Label Cases Percentage
1 income 1345 26.2% 0.2620811
2 share dividends 1237 24.1% 0.2410366
4 wealth 1291 25.2% 0.2515588
5 inheritance 1259 24.5% 0.2453235
Sysmiss 4908 NA


r21meme_skatt1_ran2


Variable label: NA
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5132] [Invalid:4908] [Range:1-2]

Value Label Cases Percentage
1 [blank] 2612 50.9% 0.5089634
2 for the richest 2520 49.1% 0.4910366
Sysmiss 4908 NA


r21meme_skatt1a


Variable label: Good/bad proposal: Increase [different types of taxes] [/for the richest]
Literal question: How good or bad do you think the proposal is?
Technical description: [Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Good proposal 1335 26.0% 0.26033541
2 Somewhat good proposal 1287 25.1% 0.25097504
3 Neither a good nor bad proposal 850 16.6% 0.16575663
4 Somewhat bad proposal 716 14.0% 0.13962559
5 Bad proposal 931 18.2% 0.18155226
97 Not answered 9 0.2% 0.00175507
98 Not asked 4912 NA


r21meme_skatt1b


Variable label: How likely to vote for party that made proposal for [increased taxes]
Pre-question text: How likely is it that you would vote for a party that made such a proposal?
Technical description: [Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Highly probable 632 12.3% 0.123244930
2 Likely 918 17.9% 0.179017161
3 Somewhat likely 879 17.1% 0.171411856
4 Neither likely nor unlikely 1082 21.1% 0.210998440
5 Somewhat unlikely 481 9.4% 0.093798752
6 Unlikely 487 9.5% 0.094968799
7 Highly unlikely 635 12.4% 0.123829953
97 Not answered 14 0.3% 0.002730109
98 Not asked 4912 NA


r21meme_skatt2_ran1


Variable label: NA
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5130] [Invalid:4910] [Range:1-5]

Value Label Cases Percentage
1 Inheritance tax should be reintroduced. 985 19.2% 0.1920078
2 Inheritance tax should be reintroduced in such a way that only those who inherit large amounts must pay. 1028 20.0% 0.2003899
3 Inheritance tax should be reintroduced in such a way that only the rich have to pay. 1047 20.4% 0.2040936
4 Inheritance tax should be reintroduced in such a way that only the richest have to pay. 1047 20.4% 0.2040936
5 Inheritance tax should be reintroduced so that the State can spend the money on reducing tax on income. 1023 19.9% 0.1994152
Sysmiss 4910 NA


r21meme_skatt2


Variable label: How good/bad is proposal for [inherance tax]?
Pre-question text:

Look at the following political proposals:

Inheritance tax should be reintroduced [NA/in such a way that only those who inherit large amounts must pay/in such a way that only the rich have to pay/in such a way that only the richest have to pay/so that the State can spend the money on reducing tax on income].
Literal question: How good or bad do you think the proposal is?
Technical description: [Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Good proposal 940 18.4% 0.183522062
2 Somewhat good proposal 1126 22.0% 0.219836002
3 Neither a good nor bad proposal 812 15.9% 0.158531824
4 Somewhat bad proposal 842 16.4% 0.164388911
5 Bad proposal 1387 27.1% 0.270792659
97 Not answered 15 0.3% 0.002928544
98 Not asked 4918 NA


r21oc1_ran1_1


Variable label: Experiment. Man 1: Religion
Technical description:

[Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]

[The alternatives ‘Christian’ and ‘Married by arranged marriage’ was excluded as valid combination in randomisation.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-2]

Value Label Cases Percentage
1 Muslim 2610 50.9% 0.5088711
2 Christian 2519 49.1% 0.4911289
Sysmiss 4911 NA


r21oc1_ran1_2


Variable label: Experiment. Man 2: Religion
Technical description:

[Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]

[The alternatives ‘Christian’ and ‘Married by arranged marriage’ was excluded as valid combination in randomisation.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-2]

Value Label Cases Percentage
1 Muslim 2588 50.5% 0.5045818
2 Christian 2541 49.5% 0.4954182
Sysmiss 4911 NA


r21oc1_ran2_1


Variable label: Experiment. Man 1: Marital status
Technical description:

[Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]

[The alternatives ‘Christian’ and ‘Married by arranged marriage’ was excluded as valid combination in randomisation.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 Unmarried 2158 42.1% 0.4207448
2 Married by love 2088 40.7% 0.4070969
3 Married by arranged marriage 883 17.2% 0.1721583
Sysmiss 4911 NA


r21oc1_ran2_2


Variable label: Experiment. Man 2: Marital status
Technical description:

[Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]

[The alternatives ‘Christian’ and ‘Married by arranged marriage’ was excluded as valid combination in randomisation.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 Unmarried 2118 41.3% 0.4129460
2 Married by love 2154 42.0% 0.4199649
3 Married by arranged marriage 857 16.7% 0.1670891
Sysmiss 4911 NA


r21oc1_ran3_1


Variable label: Experiment. Man 1: Birth country
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 Born in Norway 1719 33.5% 0.3351531
2 Born in Bosnia 1735 33.8% 0.3382726
3 Born in Syria 1675 32.7% 0.3265744
Sysmiss 4911 NA


r21oc1_ran3_2


Variable label: Experiment. Man 2: Birth country
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 Born in Norway 1683 32.8% 0.3281341
2 Born in Bosnia 1682 32.8% 0.3279392
3 Born in Syria 1764 34.4% 0.3439267
Sysmiss 4911 NA


r21oc1_ran4_1


Variable label: Experiment. Man 1: Education level
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 did not complete upper secondary school 1802 35.1% 0.3513355
2 upper secondary school education 1647 32.1% 0.3211152
3 university graduate 1680 32.8% 0.3275492
Sysmiss 4911 NA


r21oc1_ran4_2


Variable label: Experiment. Man 2: Education level
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 did not complete upper secondary school 1676 32.7% 0.3267694
2 upper secondary school education 1775 34.6% 0.3460714
3 university graduate 1678 32.7% 0.3271593
Sysmiss 4911 NA


r21oc1_ran5_1


Variable label: Experiment. Man 1: Religiosity
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 is not religious 1777 34.6% 0.3464613
2 prays occasionally 1600 31.2% 0.3119516
3 prays several times a day 1752 34.2% 0.3415871
Sysmiss 4911 NA


r21oc1_ran5_2


Variable label: Experiment. Man 2: Religiosity
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 is not religious 1765 34.4% 0.3441217
2 prays occasionally 1640 32.0% 0.3197504
3 prays several times a day 1724 33.6% 0.3361279
Sysmiss 4911 NA


r21oc1_ran6_1


Variable label: Experiment. Man 1: Gay marriage
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-2]

Value Label Cases Percentage
1 supports same-sex marriage 2594 50.6% 0.5057516
2 is against same-sex marriage 2535 49.4% 0.4942484
Sysmiss 4911 NA


r21oc1_ran6_2


Variable label: Experiment. Man 2: Gay marriage
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-2]

Value Label Cases Percentage
1 supports same-sex marriage 2526 49.2% 0.4924937
2 is against same-sex marriage 2603 50.8% 0.5075063
Sysmiss 4911 NA


r21oc1_ran7_1


Variable label: Experiment. Man 1: Gender roles
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 believes women should obey their men 1702 33.2% 0.3318386
2 believes men and women should be equal 1728 33.7% 0.3369078
3 believes women should dress conservatively 1699 33.1% 0.3312537
Sysmiss 4911 NA


r21oc1_ran7_2


Variable label: Experiment. Man 2: Gender roles
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:5129] [Invalid:4911] [Range:1-3]

Value Label Cases Percentage
1 believes women should obey their men 1753 34.2% 0.3417820
2 believes men and women should be equal 1740 33.9% 0.3392474
3 believes women should dress conservatively 1636 31.9% 0.3189706
Sysmiss 4911 NA


r21oc1_order_1


Variable label: Experiment. First attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_2


Variable label: Experiment. Second attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_3


Variable label: Experiment. Third attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_4


Variable label: Experiment. Fourth attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_5


Variable label: Experiment. Fifth attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_6


Variable label: Experiment. Sixth attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1_order_7


Variable label: Experiment. Seventh attribute to be listed.
Technical description: [Randomized if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:5129] [Invalid:4911] [Range:-]



r21oc1


Variable label: Which of two men would you rather have as a colleague?
Pre-question text:

Please consider the two profiles below carefully. Once you have considered both profiles, you can answer the question below. You will see a total of two profiles.

[The respondent was shown two randomized profiles based on r21oc1_ran1 through r21oc1_ran7]
Literal question: Which of the two men would you rather have as a colleague?
Technical description:

[Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]

[Answer list display order: Randomize]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Man 1 2440 48.4% 0.48422306
2 Man 2 2339 46.4% 0.46417940
97 Not answered 260 5.2% 0.05159754
98 Not asked 5001 NA


r21oc2


Variable label: How would you feel about having man 1 as a colleague?
Literal question: On a scale of 0 to 100, how would you feel about having man 1 as a colleague?
Post-question: Scores between 50 and 100 mean that you feel warmth and goodwill towards him; scores between 0 and 50 mean you do not feel goodwill towards him and did not think much of him. If you do not feel particularly warm or cold towards him, you can give him a score of 50.
Technical description: [Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Numeric] [Format:numeric] [Valid:4802] [Invalid:5238] [Range:0-100]



r21oc3


Variable label: How would you feel about having man 2 as a colleague?
Literal question: On a scale of 0 to 100, how would you feel about having man 2 as a colleague?
Post-question: Scores between 50 and 100 mean that you feel warmth and goodwill towards him; scores between 0 and 50 mean you do not feel goodwill towards him and did not think much of him. If you do not feel particularly warm or cold towards him, you can give him a score of 50.
Technical description: [Asked if (r19group != 3 & r20group != 6 & r16group != 6,7)]
Technical attributes: [Question type:Numeric] [Format:numeric] [Valid:4793] [Invalid:5247] [Range:0-100]



r21padkom1


Variable label: Agree/disagree: The will of the majority should govern, even at the expense of minorities
Literal question: In Norway, the will of the majority should always govern, even at the expense of the rights of minorities.
Technical description: [Asked if r16group = 6,7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely agree 218 8.7% 0.087409783
2 Somewhat agree 773 31.0% 0.309943865
3 Neither agree nor disagree 504 20.2% 0.202085004
4 Somewhat disagree 659 26.4% 0.264234162
5 Completely disagree 323 13.0% 0.129510826
97 Not answered 17 0.7% 0.006816359
98 Not asked 7546 NA


r21padkom2


Variable label: Agree/disagree: A strong political leader is good, even if rules are bend to get things done
Literal question: A strong political leader is good for Norway, even if the leader bends the rules to get things done.
Technical description: [Asked if r16group = 6,7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely agree 99 4.0% 0.03969527
2 Somewhat agree 463 18.6% 0.18564555
3 Neither agree nor disagree 322 12.9% 0.12910986
4 Somewhat disagree 865 34.7% 0.34683240
5 Completely disagree 720 28.9% 0.28869286
97 Not answered 25 1.0% 0.01002406
98 Not asked 7546 NA


r21padkom3


Variable label: Agree/disagree: Norwegian citizens should have the last word in important decisions via referendums
Literal question: In Norway, Norwegian citizens should have the last word in important political decisions via referendums.
Technical description: [Asked if r16group = 6,7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely agree 668 26.8% 0.267842823
2 Somewhat agree 789 31.6% 0.316359262
3 Neither agree nor disagree 442 17.7% 0.177225341
4 Somewhat disagree 436 17.5% 0.174819567
5 Completely disagree 139 5.6% 0.055733761
97 Not answered 20 0.8% 0.008019246
98 Not asked 7546 NA


r21padkom4


Variable label: Agree/disagree: Courts must be able to stop the government if it oversteps its authority
Literal question: In Norway, courts must be able to stop the government if it oversteps its authority.
Technical description: [Asked if r16group = 6,7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely agree 1417 56.8% 0.568163593
2 Somewhat agree 708 28.4% 0.283881315
3 Neither agree nor disagree 211 8.5% 0.084603047
4 Somewhat disagree 93 3.7% 0.037289495
5 Completely disagree 44 1.8% 0.017642342
97 Not answered 21 0.8% 0.008420209
98 Not asked 7546 NA


r21padkom5


Variable label: Agree/disagree: If the majority in Norway change their minds, the government should change its policy
Literal question: If the majority in Norway change their minds, the government should change its policy.
Technical description: [Asked if r16group = 6,7]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Completely agree 375 15.0% 0.15036087
2 Somewhat agree 889 35.6% 0.35645549
3 Neither agree nor disagree 662 26.5% 0.26543705
4 Somewhat disagree 390 15.6% 0.15637530
5 Completely disagree 151 6.1% 0.06054531
97 Not answered 27 1.1% 0.01082598
98 Not asked 7546 NA


r21tdr16


Variable label: How do you perceive the current economic situation to be in Norway?
Pre-question text:

How do you perceive the current economic situation to be in Norway?

Literal question:

Do you think it is:

Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very good 508 25.5% 0.255404726
2 Good 1031 51.8% 0.518350930
3 Quite good 259 13.0% 0.130216189
4 Neither good nor bad 93 4.7% 0.046757164
5 Quite bad 70 3.5% 0.035193565
6 Bad 15 0.8% 0.007541478
7 Very bad 7 0.4% 0.003519356
97 Not answered 6 0.3% 0.003016591
98 Not asked 8051 NA


r21tdr17


Variable label: Economic situation in [region] compared to [region]
Literal question: If you compare the economic situation in [region] with the rest of Norway, do you consider the situation in [region] as better, worse or the same?
Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 Better 484 24.3% 0.2433384
2 The same 1212 60.9% 0.6093514
3 Worse 270 13.6% 0.1357466
97 Not answered 23 1.2% 0.0115636
98 Not asked 8051 NA


r21tdr1_1


Variable label: How strong connection to: The municipality you live in
Pre-question text: How strong is your connection to:
Literal question: The municipality you live in
Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strong connection 690 34.7% 0.346907994
2 Connection 774 38.9% 0.389140271
3 Some connection 357 17.9% 0.179487179
4 Small connection 134 6.7% 0.067370538
5 No connection 20 1.0% 0.010055304
97 Not answered 14 0.7% 0.007038713
98 Not asked 8051 NA


r21tdr1_2


Variable label: How strong connection to: The county you live in
Pre-question text: How strong is your connection to:
Literal question: The county you live in
Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strong connection 427 21.5% 0.21468074
2 Connection 694 34.9% 0.34891905
3 Some connection 442 22.2% 0.22222222
4 Small connection 289 14.5% 0.14529915
5 No connection 114 5.7% 0.05731523
97 Not answered 23 1.2% 0.01156360
98 Not asked 8051 NA


r21tdr1_3


Variable label: How strong connection to: Norway
Pre-question text: How strong is your connection to:
Literal question: Norway
Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strong connection 1397 70.2% 0.702362996
2 Connection 467 23.5% 0.234791352
3 Some connection 78 3.9% 0.039215686
4 Small connection 22 1.1% 0.011060835
5 No connection 4 0.2% 0.002011061
97 Not answered 21 1.1% 0.010558069
98 Not asked 8051 NA


r21tdr19


Variable label: Agree/disagree: Should transfer resources from rich to poor parts of the country
Pre-question text:

To what extent do you agree with the following statement:

Literal question: Economic resources should be transferred from the rich parts of the country to parts that are not so rich, to ensure that everyone receives public services of the same quality.
Technical description: [Asked if r21group = 1]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 291 14.6% 0.146304676
2 Agree 688 34.6% 0.345902464
3 Somewhat agree 608 30.6% 0.305681247
4 Neither agree nor disagree 203 10.2% 0.102061337
5 Somewhat disagree 92 4.6% 0.046254399
6 Disagree 72 3.6% 0.036199095
7 Strongly disagree 22 1.1% 0.011060835
97 Not answered 13 0.7% 0.006535948
98 Not asked 8051 NA


r21tdr20_1


Variable label: Wins at least one district seat in your constituency: The Christian Democrats
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Christian Democrats
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 120 6.0% 0.06033183
2 Unlikely 329 16.5% 0.16540975
3 Quite unlikely 351 17.6% 0.17647059
4 Neither likely nor unlikely 506 25.4% 0.25439920
5 Quite likely 349 17.5% 0.17546506
6 Likely 149 7.5% 0.07491202
7 Definitely 65 3.3% 0.03267974
97 Not answered 120 6.0% 0.06033183
98 Not asked 8051 NA


r21tdr20_2


Variable label: Wins at least one district seat in your constituency: The Conservative Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Conservative Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 28 1.4% 0.01407743
2 Unlikely 36 1.8% 0.01809955
3 Quite unlikely 98 4.9% 0.04927099
4 Neither likely nor unlikely 201 10.1% 0.10105581
5 Quite likely 416 20.9% 0.20915033
6 Likely 423 21.3% 0.21266968
7 Definitely 685 34.4% 0.34439417
97 Not answered 102 5.1% 0.05128205
98 Not asked 8051 NA


r21tdr20_3


Variable label: Wins at least one district seat in your constituency: The Progressive Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Progressive Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 54 2.7% 0.02714932
2 Unlikely 107 5.4% 0.05379588
3 Quite unlikely 208 10.5% 0.10457516
4 Neither likely nor unlikely 356 17.9% 0.17898441
5 Quite likely 528 26.5% 0.26546003
6 Likely 350 17.6% 0.17596782
7 Definitely 271 13.6% 0.13624937
97 Not answered 115 5.8% 0.05781800
98 Not asked 8051 NA


r21tdr20_4


Variable label: Wins at least one district seat in your constituency: The Liberal Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Liberal Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 118 5.9% 0.05932629
2 Unlikely 300 15.1% 0.15082956
3 Quite unlikely 368 18.5% 0.18501760
4 Neither likely nor unlikely 564 28.4% 0.28355958
5 Quite likely 340 17.1% 0.17094017
6 Likely 118 5.9% 0.05932629
7 Definitely 53 2.7% 0.02664656
97 Not answered 128 6.4% 0.06435395
98 Not asked 8051 NA


r21tdr20_5


Variable label: Wins at least one district seat in your constituency: The Centre Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Centre Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 32 1.6% 0.01608849
2 Unlikely 67 3.4% 0.03368527
3 Quite unlikely 129 6.5% 0.06485671
4 Neither likely nor unlikely 295 14.8% 0.14831574
5 Quite likely 532 26.7% 0.26747109
6 Likely 444 22.3% 0.22322775
7 Definitely 384 19.3% 0.19306184
97 Not answered 106 5.3% 0.05329311
98 Not asked 8051 NA


r21tdr20_6


Variable label: Wins at least one district seat in your constituency: The Socialist Left Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Socialist Left Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 89 4.5% 0.04474610
2 Unlikely 157 7.9% 0.07893414
3 Quite unlikely 249 12.5% 0.12518854
4 Neither likely nor unlikely 465 23.4% 0.23378582
5 Quite likely 471 23.7% 0.23680241
6 Likely 262 13.2% 0.13172448
7 Definitely 172 8.6% 0.08647562
97 Not answered 124 6.2% 0.06234289
98 Not asked 8051 NA


r21tdr20_7


Variable label: Wins at least one district seat in your constituency: The Green Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Green Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 206 10.4% 0.10356963
2 Unlikely 318 16.0% 0.15987934
3 Quite unlikely 285 14.3% 0.14328808
4 Neither likely nor unlikely 448 22.5% 0.22523881
5 Quite likely 356 17.9% 0.17898441
6 Likely 179 9.0% 0.08999497
7 Definitely 79 4.0% 0.03971845
97 Not answered 118 5.9% 0.05932629
98 Not asked 8051 NA


r21tdr20_8


Variable label: Wins at least one district seat in your constituency: The Labour Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Labour Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 26 1.3% 0.01307190
2 Unlikely 23 1.2% 0.01156360
3 Quite unlikely 52 2.6% 0.02614379
4 Neither likely nor unlikely 165 8.3% 0.08295626
5 Quite likely 439 22.1% 0.22071393
6 Likely 460 23.1% 0.23127200
7 Definitely 728 36.6% 0.36601307
97 Not answered 96 4.8% 0.04826546
98 Not asked 8051 NA


r21tdr20_9


Variable label: Wins at least one district seat in your constituency: The Red Party
Pre-question text: How likely do you think it is that the following parties will win at least one district seat in your constituency?
Literal question: The Red Party
Post-question: The 19 former counties make up the constituencies.
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 235 11.8% 0.11814982
2 Unlikely 418 21.0% 0.21015586
3 Quite unlikely 391 19.7% 0.19658120
4 Neither likely nor unlikely 411 20.7% 0.20663650
5 Quite likely 239 12.0% 0.12016088
6 Likely 125 6.3% 0.06284565
7 Definitely 42 2.1% 0.02111614
97 Not answered 128 6.4% 0.06435395
98 Not asked 8051 NA


r21tdr21_1


Variable label: The following party will cross the election threshold: The Christian Democrats
Pre-question text: How likely do you think it is that the following parties will cross the election threshold (4% of the votes nationwide)?
Literal question: The Christian Democrats
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 78 3.9% 0.03921569
2 Unlikely 227 11.4% 0.11412770
3 Quite unlikely 420 21.1% 0.21116139
4 Neither likely nor unlikely 623 31.3% 0.31322272
5 Quite likely 428 21.5% 0.21518351
6 Likely 111 5.6% 0.05580694
7 Definitely 30 1.5% 0.01508296
97 Not answered 72 3.6% 0.03619910
98 Not asked 8051 NA


r21tdr21_2


Variable label: The following party will cross the election threshold: The Liberal Party
Pre-question text: How likely do you think it is that the following parties will cross the election threshold (4% of the votes nationwide)?
Literal question: The Liberal Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 82 4.1% 0.04122675
2 Unlikely 205 10.3% 0.10306687
3 Quite unlikely 458 23.0% 0.23026647
4 Neither likely nor unlikely 646 32.5% 0.32478632
5 Quite likely 368 18.5% 0.18501760
6 Likely 130 6.5% 0.06535948
7 Definitely 23 1.2% 0.01156360
97 Not answered 77 3.9% 0.03871292
98 Not asked 8051 NA


r21tdr21_3


Variable label: The following party will cross the election threshold: The Socialist Left Party
Pre-question text: How likely do you think it is that the following parties will cross the election threshold (4% of the votes nationwide)?
Literal question: The Socialist Left Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 20 1.0% 0.01005530
2 Unlikely 67 3.4% 0.03368527
3 Quite unlikely 141 7.1% 0.07088989
4 Neither likely nor unlikely 301 15.1% 0.15133233
5 Quite likely 607 30.5% 0.30517848
6 Likely 420 21.1% 0.21116139
7 Definitely 354 17.8% 0.17797888
97 Not answered 79 4.0% 0.03971845
98 Not asked 8051 NA


r21tdr21_4


Variable label: The following party will cross the election threshold: The Green Party
Pre-question text: How likely do you think it is that the following parties will cross the election threshold (4% of the votes nationwide)?
Literal question: The Green Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 103 5.2% 0.05178482
2 Unlikely 174 8.7% 0.08748115
3 Quite unlikely 277 13.9% 0.13926596
4 Neither likely nor unlikely 471 23.7% 0.23680241
5 Quite likely 599 30.1% 0.30115636
6 Likely 230 11.6% 0.11563600
7 Definitely 64 3.2% 0.03217697
97 Not answered 71 3.6% 0.03569633
98 Not asked 8051 NA


r21tdr21_5


Variable label: The following party will cross the election threshold: The Red Party
Pre-question text: How likely do you think it is that the following parties will cross the election threshold (4% of the votes nationwide)?
Literal question: The Red Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 106 5.3% 0.05329311
2 Unlikely 252 12.7% 0.12669683
3 Quite unlikely 410 20.6% 0.20613374
4 Neither likely nor unlikely 536 26.9% 0.26948215
5 Quite likely 419 21.1% 0.21065862
6 Likely 159 8.0% 0.07993967
7 Definitely 27 1.4% 0.01357466
97 Not answered 80 4.0% 0.04022122
98 Not asked 8051 NA


r21tdr22_1


Variable label: Want the following party to enter government after the election: The Christian Democrats
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Christian Democrats
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 593 29.8% 0.29813977
2 Undesirable 311 15.6% 0.15635998
3 Somewhat undesirable 240 12.1% 0.12066365
4 Neither desirable nor undesirable 336 16.9% 0.16892911
5 Somewhat desirable 207 10.4% 0.10407240
6 Desirable 130 6.5% 0.06535948
7 Highly desirable 61 3.1% 0.03066868
97 Not answered 111 5.6% 0.05580694
98 Not asked 8051 NA


r21tdr22_2


Variable label: Want the following party to enter government after the election: The Conservative Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Conservative Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 340 17.1% 0.17094017
2 Undesirable 221 11.1% 0.11111111
3 Somewhat undesirable 207 10.4% 0.10407240
4 Neither desirable nor undesirable 207 10.4% 0.10407240
5 Somewhat desirable 249 12.5% 0.12518854
6 Desirable 326 16.4% 0.16390146
7 Highly desirable 334 16.8% 0.16792358
97 Not answered 105 5.3% 0.05279035
98 Not asked 8051 NA


r21tdr22_3


Variable label: Want the following party to enter government after the election: The Progress Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Progressive Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 825 41.5% 0.41478130
2 Undesirable 257 12.9% 0.12921066
3 Somewhat undesirable 149 7.5% 0.07491202
4 Neither desirable nor undesirable 194 9.8% 0.09753645
5 Somewhat desirable 202 10.2% 0.10155857
6 Desirable 141 7.1% 0.07088989
7 Highly desirable 110 5.5% 0.05530417
97 Not answered 111 5.6% 0.05580694
98 Not asked 8051 NA


r21tdr22_4


Variable label: Want the following party to enter government after the election: The Liberal Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Liberal Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 420 21.1% 0.21116139
2 Undesirable 244 12.3% 0.12267471
3 Somewhat undesirable 228 11.5% 0.11463047
4 Neither desirable nor undesirable 410 20.6% 0.20613374
5 Somewhat desirable 296 14.9% 0.14881850
6 Desirable 204 10.3% 0.10256410
7 Highly desirable 76 3.8% 0.03821016
97 Not answered 111 5.6% 0.05580694
98 Not asked 8051 NA


r21tdr22_5


Variable label: Want the following party to enter government after the election: The Centre Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Centre Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 188 9.5% 0.09451986
2 Undesirable 141 7.1% 0.07088989
3 Somewhat undesirable 183 9.2% 0.09200603
4 Neither desirable nor undesirable 319 16.0% 0.16038210
5 Somewhat desirable 437 22.0% 0.21970840
6 Desirable 372 18.7% 0.18702866
7 Highly desirable 265 13.3% 0.13323278
97 Not answered 84 4.2% 0.04223228
98 Not asked 8051 NA


r21tdr22_6


Variable label: Want the following party to enter government after the election: The Socialist Left Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Socialist Left Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 362 18.2% 0.18200101
2 Undesirable 214 10.8% 0.10759175
3 Somewhat undesirable 201 10.1% 0.10105581
4 Neither desirable nor undesirable 294 14.8% 0.14781297
5 Somewhat desirable 291 14.6% 0.14630468
6 Desirable 272 13.7% 0.13675214
7 Highly desirable 251 12.6% 0.12619407
97 Not answered 104 5.2% 0.05228758
98 Not asked 8051 NA


r21tdr22_7


Variable label: Want the following party to enter government after the election: The Green Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Green Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 587 29.5% 0.29512318
2 Undesirable 242 12.2% 0.12166918
3 Somewhat undesirable 187 9.4% 0.09401709
4 Neither desirable nor undesirable 239 12.0% 0.12016088
5 Somewhat desirable 287 14.4% 0.14429361
6 Desirable 203 10.2% 0.10206134
7 Highly desirable 125 6.3% 0.06284565
97 Not answered 119 6.0% 0.05982906
98 Not asked 8051 NA


r21tdr22_8


Variable label: Want the following party to enter government after the election: The Labour Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Labour Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 124 6.2% 0.06234289
2 Undesirable 118 5.9% 0.05932629
3 Somewhat undesirable 158 7.9% 0.07943690
4 Neither desirable nor undesirable 246 12.4% 0.12368024
5 Somewhat desirable 331 16.6% 0.16641528
6 Desirable 477 24.0% 0.23981900
7 Highly desirable 449 22.6% 0.22574158
97 Not answered 86 4.3% 0.04323781
98 Not asked 8051 NA


r21tdr22_9


Variable label: Want the following party to enter government after the election: The Red Party
Pre-question text: To what extent do you want the following parties to enter government after the parliamentary election?
Literal question: The Red Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Not desirable at all 619 31.1% 0.31121166
2 Undesirable 257 12.9% 0.12921066
3 Somewhat undesirable 198 10.0% 0.09954751
4 Neither desirable nor undesirable 289 14.5% 0.14529915
5 Somewhat desirable 245 12.3% 0.12317748
6 Desirable 149 7.5% 0.07491202
7 Highly desirable 111 5.6% 0.05580694
97 Not answered 121 6.1% 0.06083459
98 Not asked 8051 NA


r21tdr23_1


Variable label: Following party will actually enter government after the election: The Christian Democrats
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Christian Democrats
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 274 13.8% 0.137757667
2 Unlikely 427 21.5% 0.214680744
3 Quite unlikely 436 21.9% 0.219205631
4 Neither likely nor unlikely 431 21.7% 0.216691805
5 Quite likely 189 9.5% 0.095022624
6 Likely 57 2.9% 0.028657617
7 Definitely 16 0.8% 0.008044243
97 Not answered 159 8.0% 0.079939668
98 Not asked 8051 NA


r21tdr23_2


Variable label: Following party will actually enter government after the election: The Conservative Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Conservative Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 196 9.9% 0.09854198
2 Unlikely 257 12.9% 0.12921066
3 Quite unlikely 419 21.1% 0.21065862
4 Neither likely nor unlikely 363 18.3% 0.18250377
5 Quite likely 297 14.9% 0.14932127
6 Likely 236 11.9% 0.11865259
7 Definitely 64 3.2% 0.03217697
97 Not answered 157 7.9% 0.07893414
98 Not asked 8051 NA


r21tdr23_3


Variable label: Following party will actually enter government after the election: The Progressive Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Progressive Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 416 20.9% 0.20915033
2 Unlikely 472 23.7% 0.23730518
3 Quite unlikely 376 18.9% 0.18903972
4 Neither likely nor unlikely 295 14.8% 0.14831574
5 Quite likely 172 8.6% 0.08647562
6 Likely 77 3.9% 0.03871292
7 Definitely 22 1.1% 0.01106083
97 Not answered 159 8.0% 0.07993967
98 Not asked 8051 NA


r21tdr23_4


Variable label: Following party will actually enter government after the election: The Liberal Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Liberal Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 260 13.1% 0.130718954
2 Unlikely 387 19.5% 0.194570136
3 Quite unlikely 471 23.7% 0.236802413
4 Neither likely nor unlikely 430 21.6% 0.216189040
5 Quite likely 196 9.9% 0.098541981
6 Likely 67 3.4% 0.033685269
7 Definitely 15 0.8% 0.007541478
97 Not answered 163 8.2% 0.081950729
98 Not asked 8051 NA


r21tdr23_5


Variable label: Following party will actually enter government after the election: The Centre Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Centre Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 18 0.9% 0.009049774
2 Unlikely 26 1.3% 0.013071895
3 Quite unlikely 56 2.8% 0.028154852
4 Neither likely nor unlikely 257 12.9% 0.129210659
5 Quite likely 642 32.3% 0.322775264
6 Likely 644 32.4% 0.323780794
7 Definitely 252 12.7% 0.126696833
97 Not answered 94 4.7% 0.047259930
98 Not asked 8051 NA


r21tdr23_6


Variable label: Following party will actually enter government after the election: The Socialist Left Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Socialist Left Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 62 3.1% 0.03117144
2 Unlikely 121 6.1% 0.06083459
3 Quite unlikely 234 11.8% 0.11764706
4 Neither likely nor unlikely 437 22.0% 0.21970840
5 Quite likely 600 30.2% 0.30165913
6 Likely 341 17.1% 0.17144294
7 Definitely 75 3.8% 0.03770739
97 Not answered 119 6.0% 0.05982906
98 Not asked 8051 NA


r21tdr23_7


Variable label: Following party will actually enter government after the election: The Green Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Green Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 313 15.7% 0.157365510
2 Unlikely 363 18.3% 0.182503771
3 Quite unlikely 380 19.1% 0.191050779
4 Neither likely nor unlikely 437 22.0% 0.219708396
5 Quite likely 240 12.1% 0.120663650
6 Likely 77 3.9% 0.038712921
7 Definitely 15 0.8% 0.007541478
97 Not answered 164 8.2% 0.082453494
98 Not asked 8051 NA


r21tdr23_8


Variable label: Following party will actually enter government after the election: The Labour Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Labour Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 20 1.0% 0.010055304
2 Unlikely 17 0.9% 0.008547009
3 Quite unlikely 39 2.0% 0.019607843
4 Neither likely nor unlikely 173 8.7% 0.086978381
5 Quite likely 541 27.2% 0.271995978
6 Likely 738 37.1% 0.371040724
7 Definitely 371 18.7% 0.186525892
97 Not answered 90 4.5% 0.045248869
98 Not asked 8051 NA


r21tdr23_9


Variable label: Following party will actually enter government after the election: The Red Party
Pre-question text: How likely do you think it is that the following parties will actually enter government after the upcoming parliamentary election?
Literal question: The Red Party
Technical description:

[Asked if r21group = 1]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Definitely not 465 23.4% 0.233785822
2 Unlikely 442 22.2% 0.222222222
3 Quite unlikely 391 19.7% 0.196581197
4 Neither likely nor unlikely 380 19.1% 0.191050779
5 Quite likely 96 4.8% 0.048265460
6 Likely 42 2.1% 0.021116139
7 Definitely 8 0.4% 0.004022122
97 Not answered 165 8.3% 0.082956259
98 Not asked 8051 NA


r21km_ansvar_1


Variable label: Responsible for cutting greenhouse gas emissions: The international community
Pre-question text: To what extent do you think the following stakeholders are responsible for cutting greenhouse gas emissions?
Literal question: The international community
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Not at all 19 0.9% 0.009359606
2 To a small extent 29 1.4% 0.014285714
3 To some extent 175 8.6% 0.086206897
4 To a large extent 759 37.4% 0.373891626
5 To a very large extent 1031 50.8% 0.507881773
97 Not answered 17 0.8% 0.008374384
98 Not asked 8010 NA


r21km_ansvar_2


Variable label: Responsible for cutting greenhouse gas emissions: National authorities
Pre-question text: To what extent do you think the following stakeholders are responsible for cutting greenhouse gas emissions?
Literal question: National authorities (the State)
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Not at all 25 1.2% 0.01231527
2 To a small extent 48 2.4% 0.02364532
3 To some extent 316 15.6% 0.15566502
4 To a large extent 806 39.7% 0.39704433
5 To a very large extent 810 39.9% 0.39901478
97 Not answered 25 1.2% 0.01231527
98 Not asked 8010 NA


r21km_ansvar_3


Variable label: Responsible for cutting greenhouse gas emissions: Local/regional authorities
Pre-question text: To what extent do you think the following stakeholders are responsible for cutting greenhouse gas emissions?
Literal question: Local and regional authorities (municipality and county)
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Not at all 42 2.1% 0.02068966
2 To a small extent 131 6.5% 0.06453202
3 To some extent 535 26.4% 0.26354680
4 To a large extent 797 39.3% 0.39261084
5 To a very large extent 499 24.6% 0.24581281
97 Not answered 26 1.3% 0.01280788
98 Not asked 8010 NA


r21km_ansvar_4


Variable label: Responsible for cutting greenhouse gas emissions: Private trade and industry
Pre-question text: To what extent do you think the following stakeholders are responsible for cutting greenhouse gas emissions?
Literal question: Private trade and industry
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Not at all 32 1.6% 0.01576355
2 To a small extent 75 3.7% 0.03694581
3 To some extent 435 21.4% 0.21428571
4 To a large extent 840 41.4% 0.41379310
5 To a very large extent 620 30.5% 0.30541872
97 Not answered 28 1.4% 0.01379310
98 Not asked 8010 NA


r21km_ansvar_5


Variable label: Responsible for cutting greenhouse gas emissions: Individuals
Pre-question text: To what extent do you think the following stakeholders are responsible for cutting greenhouse gas emissions?
Literal question: Individuals
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Not at all 66 3.3% 0.03251232
2 To a small extent 230 11.3% 0.11330049
3 To some extent 637 31.4% 0.31379310
4 To a large extent 673 33.2% 0.33152709
5 To a very large extent 399 19.7% 0.19655172
97 Not answered 25 1.2% 0.01231527
98 Not asked 8010 NA


r21padkom13_1


Variable label: Agree/disagree: I am able to get all public benifits I am entitled to
Pre-question text: In general, how much do you agree or disagree with the following statements?
Literal question: I am able to obtain all public benefits, services and permits that I am entitled to.
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 131 6.5% 0.064532020
2 Agree 625 30.8% 0.307881773
3 Agree somewhat 514 25.3% 0.253201970
4 Neither agree nor disagree 276 13.6% 0.135960591
5 Disagree somewhat 310 15.3% 0.152709360
6 Disagree 117 5.8% 0.057635468
7 Strongly disagree 40 2.0% 0.019704433
97 Not answered 17 0.8% 0.008374384
98 Not asked 8010 NA


r21padkom13_2


Variable label: Agree/disagree: Public admistration is too complicated for people like me to understand.
Pre-question text: In general, how much do you agree or disagree with the following statements?
Literal question: The public administration is so complicated that people like me are unable to understand what is going on within varios agencies, directorates, municipalities, and so on.
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 149 7.3% 0.07339901
2 Agree 388 19.1% 0.19113300
3 Agree somewhat 693 34.1% 0.34137931
4 Neither agree nor disagree 198 9.8% 0.09753695
5 Disagree somewhat 260 12.8% 0.12807882
6 Disagree 268 13.2% 0.13201970
7 Strongly disagree 53 2.6% 0.02610837
97 Not answered 21 1.0% 0.01034483
98 Not asked 8010 NA


r21padkom14_1


Variable label: Agree/disagree: Public servants do not care about the needs of people like med
Pre-question text: In general, how much do you agree or disagree with the following statements?
Literal question: Those who work in the public administration do not care about the needs of people like me.
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 87 4.3% 0.04285714
2 Agree 196 9.7% 0.09655172
3 Agree somewhat 419 20.6% 0.20640394
4 Neither agree nor disagree 450 22.2% 0.22167488
5 Disagree somewhat 333 16.4% 0.16403941
6 Disagree 440 21.7% 0.21674877
7 Strongly disagree 82 4.0% 0.04039409
97 Not answered 23 1.1% 0.01133005
98 Not asked 8010 NA


r21padkom14_2


Variable label: Agree/disagree: Caseworkers in public administration care only about technical aspects of cases.
Pre-question text: In general, how much do you agree or disagree with the following statements?
Literal question: Caseworkers in the public administration are only interested in the technical aspects of the case, not what those affected actually want.
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 116 5.7% 0.05714286
2 Agree 249 12.3% 0.12266010
3 Agree somewhat 558 27.5% 0.27487685
4 Neither agree nor disagree 442 21.8% 0.21773399
5 Disagree somewhat 277 13.6% 0.13645320
6 Disagree 316 15.6% 0.15566502
7 Strongly disagree 47 2.3% 0.02315271
97 Not answered 25 1.2% 0.01231527
98 Not asked 8010 NA


r21padkom15


Variable label: Generally speaking, how much confidence do you have in NAV as an institution?
Literal question: Generally speaking, how much confidence do you have in NAV as an institution?
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very high confidence 45 2.2% 0.02216749
2 High confidence 761 37.5% 0.37487685
3 Some confidence 879 43.3% 0.43300493
4 Little confidence 265 13.1% 0.13054187
5 No confidence at all 59 2.9% 0.02906404
97 Not answered 21 1.0% 0.01034483
98 Not asked 8010 NA


r21padkom16


Variable label: Generally speaking, how much would you say you know about NAV?
Literal question: Generally speaking, how much would you say you know about NAV?
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 A great deal 99 4.9% 0.04876847
2 A lot 339 16.7% 0.16699507
3 Quite a lot 748 36.8% 0.36847291
4 Not much 775 38.2% 0.38177340
5 Nothing at all 34 1.7% 0.01674877
97 Not answered 35 1.7% 0.01724138
98 Not asked 8010 NA


r21padkom17_1_1


Variable label: Personal experience with NAV in the area: Family
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Family (child benefit, parental benefit, cash grants for families with small children, benefits for single parents, child support payments) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_1_2


Variable label: Experience with NAV as next of kin in the area: Family
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Family (child benefit, parental benefit, cash grants for families with small children, benefits for single parents, child support payments) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_1_3


Variable label: No experience with NAV in the area: Family
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Family (child benefit, parental benefit, cash grants for families with small children, benefits for single parents, child support payments) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_2_1


Variable label: Personal experience with NAV in the area: Illness and injury
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Illness and injury (temporary disability benefit, rehabilitation allowance, sickness benefit) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_2_2


Variable label: Experience with NAV as next of kin in the area: Illness and injury
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Illness and injury (temporary disability benefit, rehabilitation allowance, sickness benefit) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_2_3


Variable label: No experience with NAV in the area: Illness and injury
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Illness and injury (temporary disability benefit, rehabilitation allowance, sickness benefit) 
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_3_1


Variable label: Personal experience with NAV in the area: Unemployment
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Unemployment (unemployment benefit, job searches, registration card, industrial rehabilitation)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_3_2


Variable label: Experience with NAV as next of kin in the area: Unemployment
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Unemployment (unemployment benefit, job searches, registration card, industrial rehabilitation)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_3_3


Variable label: No experience with NAV in the area: Unemployment
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Unemployment (unemployment benefit, job searches, registration card, industrial rehabilitation)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_4_1


Variable label: Personal experience with NAV in the area: Old age and disability
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Old age and disability (disability pension, retirement pension)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_4_2


Variable label: Experience with NAV as next of kin in the area: Old age and disability
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Old age and disability (disability pension, retirement pension)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_4_3


Variable label: No experience with NAV in the area: Old age and disability
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Old age and disability (disability pension, retirement pension)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_5_1


Variable label: Personal experience with NAV in the area: Social services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Social services (social assistance, financial advice, qualification programme)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_5_2


Variable label: Experience with NAV as next of kin in the area: Social services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Social services (social assistance, financial advice, qualification programme)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_5_3


Variable label: No experience with NAV in the area: Social services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Social services (social assistance, financial advice, qualification programme)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_6_1


Variable label: Personal experience with NAV in the area: Health services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Health services (exemption card scheme, aids, travel allowance)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_6_2


Variable label: Experience with NAV as next of kin in the area: Health services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Health services (exemption card scheme, aids, travel allowance)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_6_3


Variable label: No experience with NAV in the area: Health services
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Health services (exemption card scheme, aids, travel allowance)
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_7_1


Variable label: Personal experience with NAV in the area: Other matters
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Other matters
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_7_2


Variable label: Experience with NAV as next of kin in the area: Other matters
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Other matters
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom17_7_3


Variable label: No experience with NAV in the area: Other matters
Pre-question text: Do you have any experience with NAV, personally or as next of kin, in the following areas?
Literal question: Other matters
Post-question: Please tick every relevant box. 
Technical description:

[Asked if r21group = 2]

[Data withheld due to privacy considerations.]
Technical attributes: [Question type:Multi Grid] [Format:numeric] [Valid:0] [Invalid:10040] [Range:-]



r21padkom18


Variable label: Have you ever been in personal contact with a case officer in NAV?
Literal question: Have you ever been in personal contact with a case officer in NAV?
Post-question: Online chats do not count.
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Yes 1154 56.8% 0.56847291
2 No 850 41.9% 0.41871921
97 Not answered 26 1.3% 0.01280788
98 Not asked 8010 NA


r21padkom19_ran


Variable label: Experiments. Randomly selects alternative for r21padkom19
Technical description: [Randomized if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2012] [Invalid:8028] [Range:1-6]

Value Label Cases Percentage
1 Family (child benefit, parental benefit, cash grants for families with small children, benefits for single parents, child support payments) 345 17.1% 0.1714712
2 Illness and injury (temporary disability benefit, rehabilitation allowance, sickness benefit) 349 17.3% 0.1734592
3 Unemployment (unemployment benefit, job searches, registration card, industrial rehabilitation) 317 15.8% 0.1575547
4 Old age and disability (disability pension, retirement pension) 337 16.7% 0.1674950
5 Social services (social assistance, financial advice, qualification programme) 303 15.1% 0.1505964
6 Health services (exemption card scheme, aids, travel allowance) 361 17.9% 0.1794235
Sysmiss 8028 NA


r21padkom19


Variable label: To what extent case officers in NAV are influenced by personal attitudes in cases regarding [different areas]
Literal question: To what extent do you think that case officers in NAV let themselves be influenced by their own personal attitudes when they make decisions in cases about [family (child benefit, parental benefit, cash grants for families with small children, benefits for single parents, child support payments/illness and injury (temporary disability benefit, rehabilitation allowance, sickness benefit)/unemployment (unemployment benefit, job searches, registration card, industrial rehabilitation)/old age and disability (disability pension, retirement pension)/social services (social assistance, financial advice, qualification programme)/health services (exemption card scheme, aids, travel allowance)]?
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 To a very great extent 63 3.1% 0.03103448
2 To a great extent 215 10.6% 0.10591133
3 To some extent 863 42.5% 0.42512315
4 To a small extent 758 37.3% 0.37339901
5 Not at all 96 4.7% 0.04729064
97 Not answered 35 1.7% 0.01724138
98 Not asked 8010 NA


r21padkom20


Variable label: How much would you say you know about machine learning and artificial intelligence?
Pre-question text:

We now want to ask about your attitudes towards the use of machine learning in public administration. Machine learning is also often referred to as artificial intelligence.

Using machine learning involves getting computers to learn how to solve tasks based on data. Computers can often become extremely accurate, although this typically requires a lot of data. Today, machine learning provides the basis for everything from automatic voice recognition to driverless cars.

In some cases, public agencies, including NAV, uses machine learning to help make decisions in cases for which they are responsible. The aim is to reduce costs and processing time, and to make decisions better and more accurate. One example might be to teach a computer to predict approximately how long a person will be on sick leave based on information about the disease and the person. A case officer can then use this to choose appropriate measures.

Literal question: Generally speaking, how much would you say you know about machine learning and artificial intelligence?
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 A great deal 110 2.8% 0.027721774
2 A lot 432 10.9% 0.108870968
3 Quite a lot 897 22.6% 0.226058468
4 Not much 2055 51.8% 0.517893145
5 Nothing at all 449 11.3% 0.113155242
97 Not answered 25 0.6% 0.006300403
98 Not asked 6072 NA


r21padkom21


Variable label: Are your interests better/worse safeguarded if machine learning is used in NAV?
Pre-question text: Let’s say that you were in a situation where you had to apply to NAV for financial support.
Literal question: Do you think that your interests would be safeguarded better or worse if the case officer used machine learning and artificial intelligence as help in making a decision about financial support?
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very much better 11 0.5% 0.005418719
2 Much better 91 4.5% 0.044827586
3 Somewhat better 412 20.3% 0.202955665
4 Neither better nor worse 830 40.9% 0.408866995
5 Somewhat worse 407 20.0% 0.200492611
6 Much worse 174 8.6% 0.085714286
7 Very much worse 62 3.1% 0.030541872
97 Not answered 43 2.1% 0.021182266
98 Not asked 8010 NA


r21padkom24


Variable label: Would you accept a work preparation course offered by NAV?
Pre-question text: First, we ask you to imagine that you are in a situation where, as a job seeker registered with NAV, you are offered a work preparation course.
Literal question: Do you think you would accept it?
Post-question: If you are not sure, please choose the option that is most likely.
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Yes, I would have accepted a work preparation course 1666 82.1% 0.8206897
2 No, I wouldn't have accepted a work preparation course 309 15.2% 0.1522167
97 Not answered 55 2.7% 0.0270936
98 Not asked 8010 NA


r21padkom25_1


Variable label: Machine learning in NAV may use: Data about job seeker’s health issues
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: The extent to which the job seeker states that they have health issues
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 272 13.4% 0.13399015
2 Appropriate 589 29.0% 0.29014778
3 Somewhat appropriate 584 28.8% 0.28768473
4 Not very appropriate 316 15.6% 0.15566502
5 Not appropriate at all 152 7.5% 0.07487685
97 Not answered 117 5.8% 0.05763547
98 Not asked 8010 NA


r21padkom25_2


Variable label: Machine learning in NAV may use: Data about job seeker’s other issues
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: The extent to which the job seeker states that they have other issues that prevent them from working
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 309 15.2% 0.15221675
2 Appropriate 655 32.3% 0.32266010
3 Somewhat appropriate 543 26.7% 0.26748768
4 Not very appropriate 278 13.7% 0.13694581
5 Not appropriate at all 127 6.3% 0.06256158
97 Not answered 118 5.8% 0.05812808
98 Not asked 8010 NA


r21padkom25_3


Variable label: Machine learning in NAV may use: Data about job seeker’s education
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Education: The extent to which the job seeker has completed approved education in Norway
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 619 30.5% 0.30492611
2 Appropriate 783 38.6% 0.38571429
3 Somewhat appropriate 359 17.7% 0.17684729
4 Not very appropriate 107 5.3% 0.05270936
5 Not appropriate at all 53 2.6% 0.02610837
97 Not answered 109 5.4% 0.05369458
98 Not asked 8010 NA


r21padkom25_4


Variable label: Machine learning in NAV may use: Data about job seeker’s work history
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Work history: Has the job seeker been in continuous work for 6 months in the last 12 months?
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 389 19.2% 0.19162562
2 Appropriate 724 35.7% 0.35665025
3 Somewhat appropriate 519 25.6% 0.25566502
4 Not very appropriate 195 9.6% 0.09605911
5 Not appropriate at all 89 4.4% 0.04384236
97 Not answered 114 5.6% 0.05615764
98 Not asked 8010 NA


r21padkom25_5


Variable label: Machine learning in NAV may use: Data about job seeker’s age
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Age
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 345 17.0% 0.16995074
2 Appropriate 591 29.1% 0.29113300
3 Somewhat appropriate 563 27.7% 0.27733990
4 Not very appropriate 289 14.2% 0.14236453
5 Not appropriate at all 125 6.2% 0.06157635
97 Not answered 117 5.8% 0.05763547
98 Not asked 8010 NA


r21padkom25_6


Variable label: Machine learning in NAV may use: Data about job seeker’s sex
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Sex
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 279 13.7% 0.13743842
2 Appropriate 425 20.9% 0.20935961
3 Somewhat appropriate 436 21.5% 0.21477833
4 Not very appropriate 387 19.1% 0.19064039
5 Not appropriate at all 387 19.1% 0.19064039
97 Not answered 116 5.7% 0.05714286
98 Not asked 8010 NA


r21padkom25_7


Variable label: Machine learning in NAV may use: Data about job seeker’s nationality
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: The job seeker’s nationality
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 219 10.8% 0.10788177
2 Appropriate 423 20.8% 0.20837438
3 Somewhat appropriate 523 25.8% 0.25763547
4 Not very appropriate 455 22.4% 0.22413793
5 Not appropriate at all 293 14.4% 0.14433498
97 Not answered 117 5.8% 0.05763547
98 Not asked 8010 NA


r21padkom25_8


Variable label: Machine learning in NAV may use: Data about job seeker’s place of residence
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Place of residence: Where in the country does the job seeker live?
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 476 23.4% 0.23448276
2 Appropriate 696 34.3% 0.34285714
3 Somewhat appropriate 441 21.7% 0.21724138
4 Not very appropriate 179 8.8% 0.08817734
5 Not appropriate at all 120 5.9% 0.05911330
97 Not answered 118 5.8% 0.05812808
98 Not asked 8010 NA


r21padkom25_9


Variable label: Machine learning in NAV may use: Data about job seeker’s criminal record
Pre-question text:

Access to job-oriented measures is needs-based. The case officer will decide which measures a job seeker will be offered based on an individual assessment of their needs. Such assessments have previously been made by the case officer alone. Today, NAV is testing machine learning as a means of assisting case officers with proposals in such assessments.

Given that this helps to ensure that proposals are more accurate, how appropriate do you think it is that in connection with machine learning a computer will process the following data about the job seeker?

Literal question: Criminal record: Has the job seeker been convicted of criminal acts?
Technical description:

[Asked if r21group = 2]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Highly appropriate 424 20.9% 0.20886700
2 Appropriate 562 27.7% 0.27684729
3 Somewhat appropriate 473 23.3% 0.23300493
4 Not very appropriate 303 14.9% 0.14926108
5 Not appropriate at all 149 7.3% 0.07339901
97 Not answered 119 5.9% 0.05862069
98 Not asked 8010 NA


r21padkom29_ran


Variable label: NA
Technical description: [Randomized if r21group = 2]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1982] [Invalid:8058] [Range:1-2]

Value Label Cases Percentage
1 As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support. 1043 52.6% 0.5262361
2 [blank] 939 47.4% 0.4737639
Sysmiss 8058 NA


r21padkom29_1


Variable label: How important that case officer in NAV has: Same level of education as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same level of education as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 109 5.4% 0.05369458
2 Important 382 18.8% 0.18817734
3 Somewhat important 519 25.6% 0.25566502
4 Not very important 555 27.3% 0.27339901
5 Not important at all 368 18.1% 0.18128079
97 Not answered 97 4.8% 0.04778325
98 Not asked 8010 NA


r21padkom29_2


Variable label: How important that case officer in NAV is: From the same region as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: From the same region as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 38 1.9% 0.01871921
2 Important 162 8.0% 0.07980296
3 Somewhat important 277 13.6% 0.13645320
4 Not very important 717 35.3% 0.35320197
5 Not important at all 737 36.3% 0.36305419
97 Not answered 99 4.9% 0.04876847
98 Not asked 8010 NA


r21padkom29_3


Variable label: How important that case officer in NAV has: Same sex as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same sex as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 16 0.8% 0.007881773
2 Important 76 3.7% 0.037438424
3 Somewhat important 211 10.4% 0.103940887
4 Not very important 721 35.5% 0.355172414
5 Not important at all 899 44.3% 0.442857143
97 Not answered 107 5.3% 0.052709360
98 Not asked 8010 NA


r21padkom29_4


Variable label: How important that case officer in NAV has: Same religious fatih as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same religious faith as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 30 1.5% 0.01477833
2 Important 65 3.2% 0.03201970
3 Somewhat important 163 8.0% 0.08029557
4 Not very important 658 32.4% 0.32413793
5 Not important at all 1014 50.0% 0.49950739
97 Not answered 100 4.9% 0.04926108
98 Not asked 8010 NA


r21padkom29_5


Variable label: How important that case officer in NAV is: About the same age as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: About the same age as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 18 0.9% 0.008866995
2 Important 112 5.5% 0.055172414
3 Somewhat important 421 20.7% 0.207389163
4 Not very important 676 33.3% 0.333004926
5 Not important at all 699 34.4% 0.344334975
97 Not answered 104 5.1% 0.051231527
98 Not asked 8010 NA


r21padkom29_6


Variable label: How important that case officer in NAV has: Same ethnic origin as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same ethnic origin as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 51 2.5% 0.02512315
2 Important 143 7.0% 0.07044335
3 Somewhat important 308 15.2% 0.15172414
4 Not very important 612 30.1% 0.30147783
5 Not important at all 812 40.0% 0.40000000
97 Not answered 104 5.1% 0.05123153
98 Not asked 8010 NA


r21padkom29_7


Variable label: How important that case officer in NAV has: Same political standpoint as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same political standpoint as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 13 0.6% 0.006403941
2 Important 53 2.6% 0.026108374
3 Somewhat important 224 11.0% 0.110344828
4 Not very important 713 35.1% 0.351231527
5 Not important at all 920 45.3% 0.453201970
97 Not answered 107 5.3% 0.052709360
98 Not asked 8010 NA


r21padkom29_8


Variable label: How important that case officer in NAV has: Same type of work experience as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same type of work experience as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 43 2.1% 0.02118227
2 Important 201 9.9% 0.09901478
3 Somewhat important 479 23.6% 0.23596059
4 Not very important 593 29.2% 0.29211823
5 Not important at all 615 30.3% 0.30295567
97 Not answered 99 4.9% 0.04876847
98 Not asked 8010 NA


r21padkom29_9


Variable label: How important that case officer in NAV has: Same sexual orientation as you
Pre-question text:

Let’s say that you were in a situation where you had to apply to NAV for financial support. If you could choose a case officer to safeguard your interests in NAV, how important do you think it would be for the person to have the following characteristics?

[blank / As support in the decision-making process, the case officer uses artificial intelligence, based on machine learning, which recommends who should receive support.]
Literal question: Same sexual orientation as you
Technical description: [Asked if r21group = 2]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very important 10 0.5% 0.004926108
2 Important 45 2.2% 0.022167488
3 Somewhat important 77 3.8% 0.037931034
4 Not very important 459 22.6% 0.226108374
5 Not important at all 1334 65.7% 0.657142857
97 Not answered 105 5.2% 0.051724138
98 Not asked 8010 NA


r21padkom22


Variable label: How concerned about the use of machine learning in public administration?
Literal question:

How concerned are you about the use of machine learning and artificial intelligence in public administration?

Post-question: You will have the opportunity to justify your answer in the next page.
Technical description: [Asked if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very concerned 103 5.3% 0.05306543
2 Concerned 360 18.5% 0.18547141
3 Somewhat concerned 806 41.5% 0.41524987
4 Not particularly concerned 563 29.0% 0.29005667
5 Not at all concerned 97 5.0% 0.04997424
97 Not answered 12 0.6% 0.00618238
98 Not asked 8099 NA


r21padkom23


Variable label: Open: Why you answered like you did to [R21PADKOM22]
Pre-question text:

In the previous question you answered that you were [R21PADKOM22_] about the use of machine learning and artificial intelligence in public administration.

Literal question:

Why is that?

Technical description:

[Asked if r21group = 3 & r21padkom22 is answered]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21padkom26_ran


Variable label: Randomly selects alternative for r21PADKOM26
Technical description: [Randomized if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1941] [Invalid:8099] [Range:0-1]

Value Label Cases Percentage
0 men than women 965 49.7% 0.4971664
1 women than men 976 50.3% 0.5028336
Sysmiss 8099 NA


r21padkom26_ran_contra


Variable label: The opposite of av r21PADKOM26_ran
Technical description: [Takes the oposite value of r21padkom26_ran]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1941] [Invalid:8099] [Range:0-1]

Value Label Cases Percentage
1 men than women 976 50.3% 0.5028336
0 women than men 965 49.7% 0.4971664
Sysmiss 8099 NA


r21padkom26


Variable label: Which of two machine learning models in NAV seems the fairest?
Pre-question text:

A realistic example of where machine learning can be used in public administration is when NAV decides which people on sick leave will be offered a dialogue meeting with NAV. A dialogue meeting is a conversation between NAV and the person on sick leave that is regarded as positive for the person on sick leave’s chances of returning to work.

Imagine we can choose between two alternative machine learning models for choosing who will be offered a dialogue meeting.

Neither of the models is perfect but they are imperfect in different ways.

The first model is the most accurate. However, from among those who need a dialogue meeting, more [women than men/men than women] are offered a dialogue meeting. Thus, the proportion who need a dialogue meeting but are not offered one is greater among [men than women/ women than men].

The second model ensures that the proportion of women and men on sick leave called in for a dialogue meeting is the same. However, it is less accurate overall, such that fewer people who need a dialogue meeting are called in. This applies to both women and men.

Literal question: If the choice was between these two models only, which seems the fairest to you?
Technical description: [Asked if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 The first model seems the fairest 870 44.8% 0.44822257
2 The second model seems the fairest 957 49.3% 0.49304482
97 Not answered 114 5.9% 0.05873261
98 Not asked 8099 NA


r21padkom27


Variable label: Open: Can you give the reasons for your answer to [r21PADKOM26]?
Literal question: Can you give the reasons for your answer?
Technical description:

[Asked if r21group = 3 & r21padkom26 is answered]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21padkom28


Variable label: Use of artificial intelligence in public administration or not, given the consequences in sum and for groups?
Pre-question text: Many decisions in public administration require the exercise of judgement based on an overall assessment of the individual case. If artificial intelligence is adopted, decisions made with the assistance of machine learning will probably be more accurate, thereby increasing the proportion of correct decisions. At the same time, a computer cannot be completely accurate either. There is also reason to believe that the remaining proportion of incorrect decisions disproportionately affects some groups in society when one uses machine learning and artificial intelligence. This is due to the great variation in how human case officers exercise judgement, while for a computer there is no variation.
Literal question: Generally speaking, which do you prefer in such situations? Using artificial intelligence (which leads to many more correct decisions in exchange for the fact that it is always the same ones who are subject to incorrect decisions), or not using artificial intelligence (which leads to many fewer correct decisions in exchange for the ones who are subject to incorrect decisions varying).
Technical description:

[Asked if r21group = 3]

[Answer list display order: Randomize]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Use artificial intelligence 871 44.9% 0.44873776
2 Do not use artificial intelligence 978 50.4% 0.50386399
97 Not answered 92 4.7% 0.04739825
98 Not asked 8099 NA


r21padkom32_ran


Variable label: Randomly selects alternative for r21PADKOM32.
Technical description: [Randomized if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1925] [Invalid:8115] [Range:1-4]

Value Label Cases Percentage
1 promoting a message that the so-called gay lobby is destroying Norwegian society 478 24.8% 0.2483117
2 promoting a message that multiculturalism is destroying Norwegian society 422 21.9% 0.2192208
3 promoting a message that Islam and Muslim immigration pose a threat to the rights of women and gays 538 27.9% 0.2794805
4 burning the Koran 487 25.3% 0.2529870
Sysmiss 8115 NA


r21padkom32


Variable label: How acceptable that counter-demonstrators physically attack to prevent far right activists?
Pre-question text: Imagine the following scenario. During a public demonstration, a group of counter-demonstrators physically attack activists from the far right to prevent them from [promoting a message that the so-called gay lobby is destroying Norwegian society/promoting a message that multiculturalism is destroying Norwegian society/promoting a message that Islam and Muslim immigration pose a threat to the rights of women and gays/burning the Koran].
Literal question: How acceptable or unacceptable do you think it is for the counter-demonstrators to physically attack activists from the far right to prevent them from doing this?
Technical description: [Asked if r21padkom32_ran = 1,2,3,4 & r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Highly acceptable 35 1.8% 0.01818182
2 Acceptable 31 1.6% 0.01610390
3 Somewhat acceptable 75 3.9% 0.03896104
4 Neither acceptable nor unacceptable 84 4.4% 0.04363636
5 Somewhat unacceptable 107 5.6% 0.05558442
6 Unacceptable 698 36.3% 0.36259740
7 Highly unacceptable 876 45.5% 0.45506494
97 Not answered 19 1.0% 0.00987013
98 Not asked 8115 NA


r21padkom33


Variable label: Agree/disagree: Far right activists should be allowed to rent community centres in my area to hold meetings
Pre-question text: To what extent do you agree or disagree with the following statement:
Literal question: Activist groups from the far right should be allowed to rent community centres in my local area to hold meetings for their members and sympathisers.
Technical description: [Asked if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 115 5.9% 0.05924781
2 Agree 314 16.2% 0.16177228
3 Somewhat agree 249 12.8% 0.12828439
4 Neither agree nor disagree 331 17.1% 0.17053065
5 Somewhat disagree 237 12.2% 0.12210201
6 Disagree 368 19.0% 0.18959299
7 Strongly disagree 288 14.8% 0.14837713
97 Not answered 39 2.0% 0.02009274
98 Not asked 8099 NA


r21padkom6


Variable label: By how much do you think Norway has cut its greenhouse gas emissions from 1990 to 2019?
Pre-question text: On the next question, please give us your best guess and do not look up the answer. The government’s goal is for Norwegian greenhouse gas emissions to be 50% lower than they were in 1990 by 2030.
Literal question:

By how much do you think Norway has cut its greenhouse gas emissions so far from 1990 to 2019?

Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Numeric] [Format:numeric] [Valid:1943] [Invalid:8097] [Range:0-100]



r21padkom7_ran


Variable label: NA
Technical description: [Randomized if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1984] [Invalid:8056] [Range:1-4]

Value Label Cases Percentage
1 We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. 523 26.4% 0.2636089
2 We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that in 2019 Norway’s emissions were about the same as in 1990. Norway has only cut about 3% of its greenhouse gas emissions in the past 30 years. 491 24.7% 0.2474798
3 We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that in 2019 Norway’s emissions were about the same as in 1990. Norway has only cut about 3% of its greenhouse gas emissions in the past 30 years. Over the same time period, Sweden has cut 30% of its emissions, and the EU countries have cut an average of 26%. 473 23.8% 0.2384073
4 We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that about 97% of climate scientists now agree that rising global temperatures are mainly due to human activity. The expected consequences of global warming include an increase in extreme weather events, such as droughts, floods, and storms. 497 25.1% 0.2505040
Sysmiss 8056 NA


r21padkom7


Variable label: Have you heard about recent item in the news about [report about greenhouse gas emissions]?
Pre-question text: [We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions./ We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that in 2019 Norway’s emissions were about the same as in 1990. Norway has only cut about 3% of its greenhouse gas emissions in the past 30 years./ We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that in 2019 Norway’s emissions were about the same as in 1990. Norway has only cut about 3% of its greenhouse gas emissions in the past 30 years. Over the same time period, Sweden has cut 30% of its emissions, and the EU countries have cut an average of 26%./ We also want to ask you about an item that has been in the news recently. The news item was about a report that was recently published about global warming and Norway’s greenhouse gas emissions. The report said that about 97% of climate scientists now agree that rising global temperatures are mainly due to human activity. The expected consequences of global warming include an increase in extreme weather events, such as droughts, floods, and storms.]
Literal question: Have you heard about a news item like this? 
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 Yes 794 39.2% 0.39248641
2 No 857 42.4% 0.42362827
3 Don't know 323 16.0% 0.15966387
97 Not answered 49 2.4% 0.02422145
98 Not asked 8017 NA


r21padkom8_1


Variable label: Agree/disagree: The government is doing enough to cut Norway’s greenhouse gas emissions
Pre-question text: Please read the following statements on climate policy and state the extent to which you agree or disagree with them:
Literal question: The government is doing enough to cut Norway’s greenhouse gas emissions.
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strongly agree 121 6.0% 0.05981216
2 Agree 532 26.3% 0.26297578
3 Disagree 780 38.6% 0.38556599
4 Strongly disagree 390 19.3% 0.19278300
5 Don't know 150 7.4% 0.07414731
97 Not answered 50 2.5% 0.02471577
98 Not asked 8017 NA


r21padkom8_2


Variable label: Agree/disagree: The carbon tax should be tripled by 2030, making it considerably more expensive to emit CO2
Pre-question text: Please read the following statements on climate policy and state the extent to which you agree or disagree with them:
Literal question: The carbon tax should be tripled by 2030, making it considerably more expensive to emit CO2.
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strongly agree 170 8.4% 0.08403361
2 Agree 664 32.8% 0.32822541
3 Disagree 561 27.7% 0.27731092
4 Strongly disagree 334 16.5% 0.16510133
5 Don't know 240 11.9% 0.11863569
97 Not answered 54 2.7% 0.02669303
98 Not asked 8017 NA


r21padkom8_3


Variable label: Agree/disagree: The Norwegian oil and gas industry should be phased out within the next 15 years
Pre-question text: Please read the following statements on climate policy and state the extent to which you agree or disagree with them:
Literal question: The Norwegian oil and gas industry should be phased out within the next 15 years.
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strongly agree 172 8.5% 0.08502224
2 Agree 422 20.9% 0.20860109
3 Disagree 623 30.8% 0.30795848
4 Strongly disagree 537 26.5% 0.26544736
5 Don't know 215 10.6% 0.10627781
97 Not answered 54 2.7% 0.02669303
98 Not asked 8017 NA


r21padkom8_4


Variable label: Agree/disagree: Could take part in a demonstration to get the government to take action on the climate
Pre-question text: Please read the following statements on climate policy and state the extent to which you agree or disagree with them:
Literal question: I could take part in a demonstration to get the government to take more action on the climate.
Technical description: [Asked if r21group = 4]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Strongly agree 119 5.9% 0.05882353
2 Agree 334 16.5% 0.16510133
3 Disagree 542 26.8% 0.26791893
4 Strongly disagree 679 33.6% 0.33564014
5 Don't know 297 14.7% 0.14681167
97 Not answered 52 2.6% 0.02570440
98 Not asked 8017 NA


r21padkom10_articles


Variable label: Experiment: List of articles shown
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:3280] [Invalid:6760] [Range:-]



r21padkom10_position


Variable label: Experiment: Article display order
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:10040] [Invalid:0] [Range:-]



r21padkom10_time_1


Variable label: Experiment session 1: Time spent reading articles
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:3186] [Invalid:6854] [Range:-]



r21padkom10_time_2


Variable label: Experiment session 2: Time spent reading articles
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:250] [Invalid:9790] [Range:-]



r21padkom10_time_3


Variable label: Experiment session 3: Time spent reading articles
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:49] [Invalid:9991] [Range:-]



r21padkom10_time_fp_1


Variable label: Experiment session 1: Time spent on front page
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Numeric] [Format:character] [Valid:3186] [Invalid:6854] [Range:-]



r21padkom10_time_fp_2


Variable label: Experiment session 2: Time spent on front page
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Numeric] [Format:character] [Valid:250] [Invalid:9790] [Range:-]



r21padkom10_time_fp_3


Variable label: Experiment session 3: Time spent on front page
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Numeric] [Format:character] [Valid:49] [Invalid:9991] [Range:-]



r21padkom10_click_order_session_1


Variable label: Experiment session 1: Article click order
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:2690] [Invalid:7350] [Range:-]



r21padkom10_click_order_session_2


Variable label: Experiment session 2: Article click order
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:189] [Invalid:9851] [Range:-]



r21padkom10_click_order_session_3


Variable label: Experiment session 3: Article click order
Pre-question text:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Literal question:

For the next two minutes, you will be able to click on and read news on a news site reminiscent of an ordinary Norwegian news site. The news items are reminiscent of and based on real items in Norwegian online newspapers.

Please click on and read the items you want to read like you normally would when you read news online. Click on the headlines to read the articles and “To front page” to return to the front page.

The survey will automatically move on to the next question when two minutes have passed. You will not have time to read all of the articles carefully before the time runs out.
Technical attributes: [Question type:Open] [Format:character] [Valid:26] [Invalid:10014] [Range:-]



r21padkom10_clock_sessiondata_1


Variable label: Time left upon ending experiment. First session
Pre-question text: Time left upon ending experiment. First session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:3186] [Invalid:6854] [Range:-]



r21padkom10_clock_sessiondata_2


Variable label: Time left upon ending experiment. Second session
Pre-question text: Time left upon ending experiment. Second session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:250] [Invalid:9790] [Range:-]



r21padkom10_clock_sessiondata_3


Variable label: Time left upon ending experiment. Last session
Pre-question text: Time left upon ending experiment. Last session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:49] [Invalid:9991] [Range:-]



r21padkom10_endby_sessiondata_1


Variable label: Reason for ending experiment. First session
Pre-question text: Reason for ending experiment. First session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:3202] [Invalid:6838] [Range:-]



r21padkom10_endby_sessiondata_2


Variable label: Reason for ending experiment. Second session
Pre-question text: Reason for ending experiment. Second session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:251] [Invalid:9789] [Range:-]



r21padkom10_endby_sessiondata_3


Variable label: Reason for ending experiment. Last session
Pre-question text: Reason for ending experiment. Last session
Technical attributes: [Question type:Open Text List] [Format:character] [Valid:49] [Invalid:9991] [Range:-]



r21padkom10_group


Variable label: Treatment group assigned at random.
Pre-question text: Experiment. Treatment group assigned at random.
Literal question:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Technical description: [Randomized if r21group = 3,4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:3284] [Invalid:6756] [Range:1-9]

Value Label Cases Percentage
1 Group 1 - Baseline 348 10.6% 0.1059683
2 Group 2 - Negative relevant 343 10.4% 0.1044458
3 Group 3 - Positive relevant 357 10.9% 0.1087089
4 Group 4 - Negative visible 378 11.5% 0.1151035
5 Group 5 - Positive visible 388 11.8% 0.1181486
6 Group 6 - Negative relevant visible 389 11.8% 0.1184531
7 Group 7 - Positive relevant visible 352 10.7% 0.1071864
8 Group 8 - Negative visible + other article relevant 350 10.7% 0.1065773
9 Group 9 - Positive visible + other article relevant 379 11.5% 0.1154080
Sysmiss 6756 NA


r21padkom10_angle


Variable label: Indicates whether the treatment article has a negative or positive angle.
Pre-question text:

Experiment. Indicates whether the treatment article has a negative or positive angle.

Based on r21padkom10_group:

positive [3, 5, 7, 9]

negative [2, 4, 6, 8]
Literal question:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Technical attributes: [Question type:Single] [Format:numeric] [Valid:2936] [Invalid:7104] [Range:1-2]

Value Label Cases Percentage
1 Positive 1476 50.3% 0.5027248
2 Negative 1460 49.7% 0.4972752
Sysmiss 7104 NA


r21padkom10_relevance


Variable label: Indicates whether the treatment article is geographically relevant to the respondent.
Pre-question text:

Experiment. Indicates whether the treatment article is geographically relevant to the respondent.

Based on r21padkom10_group:

Relevant [2, 3, 6, 7, 8, 9]

Not relevant [1, 4, 5]
Literal question:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Technical attributes: [Question type:Single] [Format:numeric] [Valid:3284] [Invalid:6756] [Range:0-1]

Value Label Cases Percentage
1 Yes - relevance in treatment (geography) 1441 43.9% 0.4387942
0 No - relevance not in treatment (geography) 1843 56.1% 0.5612058
Sysmiss 6756 NA


r21padkom10_enlarged


Variable label: Indicates whether the treatment article was highlited with a large image on the front page.
Pre-question text:

Experiment. Indicates whether the treatment article was highlited with a large image on the front page.

Based on r21padkom10_group:

Large image [4, 5, 6, 7, 8, 9]

Small image [0, 1, 2, 3]
Literal question:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Technical attributes: [Question type:Single] [Format:numeric] [Valid:3284] [Invalid:6756] [Range:0-1]

Value Label Cases Percentage
1 Yes - enhanced visibility 2236 68.1% 0.680877
0 No - not enhanced visibility 1048 31.9% 0.319123
Sysmiss 6756 NA


r21padkom10_order_option


Variable label: Indicates the method for sorting the news articles.
Pre-question text:

Experiment. Indicates the method for sorting the news articles.

Based on r21padkom10_group:

Random order [0, 1, 2, 3]

Treatment article was displayed first [4, 5, 6, 7, 8, 9]
Literal question:

Experiment. The respondents were shown a «news site» with eight fictitious news articles. Two of the articles ere treatment articles, one negative and one positive. The rest were neutral.

The respondents were assigned at random to one of nine groups, varying on article sorting method, visual prominence of the treatment articles on the front page and geographic relevance for the respondent.

The respondents could click and read the articles as they wished, and could at any time return to the front page. Two minutes into the experiment, the respondents were automatically sent to the next question. The respondents could enter the question as many times as they wished, with the first, second and last session being saved.

Technical attributes: [Question type:Single] [Format:numeric] [Valid:3284] [Invalid:6756] [Range:1-2]

Value Label Cases Percentage
1 Group 0, 1, 2, 3: All in random order 1048 31.9% 0.319123
2 Group 4, 5, 6, 7, 8 og 9: Treatment-article on top of page 2236 68.1% 0.680877
Sysmiss 6756 NA


r21padkom11


Variable label: How close to/far from is the place mentioned in [r21padkom10_header] from here you live?
Pre-question text: The title of the article below mentions a place.
Literal question: How close to or far from where you live is this?
Technical description: [Asked if r21padkom10_relevance = 1 & r21group = 3,4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Very close/I live here 943 65.4% 0.65440666
2 Somewhat close 186 12.9% 0.12907703
3 Neither close nor far away 130 9.0% 0.09021513
4 Somewhat far away 62 4.3% 0.04302568
5 Very far away 33 2.3% 0.02290076
6 I haven't heard of this place. 65 4.5% 0.04510756
97 Not answered 22 1.5% 0.01526718
98 Not asked 8599 NA


r21padkom12_ran


Variable label: Randomly selects if the respondents is shown a negative or positive article.
Technical description: [Randomized if r21group = 3,4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:1843] [Invalid:8197] [Range:1-2]

Value Label Cases Percentage
1 Positive 929 50.4% 0.5040695
2 Negative 914 49.6% 0.4959305
Sysmiss 8197 NA


r21padkom12_articleheader


Variable label: Randomly selected headline for r21padkom12
Technical description:

[Randomized if r21group = 3,4]

[Text data witheld due to privacy considerations. However, data can be made available for researchers after contacting DIGSSCORE/University of Bergen.]
Technical attributes: [Question type:Open] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21padkom12


Variable label: To what extent does [r21padkom12_articleheader] portray immigration in a negative/positive way?
Pre-question text: [r21padkom12_articleheader]
Literal question: To what extent do you think the title of the article below portrays immigration in a negative or positive way?
Technical description: [Asked if r21padkom10_relevance = 0 & r21group = 3,4]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Portrays immigration in a very positive way 74 4.0% 0.04015193
2 Portrays immigration in a positive way 532 28.9% 0.28865979
3 Portrays immigration in neither a positive nor a negative way 692 37.5% 0.37547477
4 Portrays immigration in a negative way 410 22.2% 0.22246337
5 Portrays immigration in a very negative way 82 4.4% 0.04449267
97 Not answered 53 2.9% 0.02875746
98 Not asked 8197 NA


r21km_fly


Variable label: How often did you travel by air in connection with holiday travel before the Covid-19 pandemic?
Literal question: If you think back to before the Covid-19 pandemic, how often would you estimate that you travelled by air in connection with holiday travel?
Post-question:

If you choose the top option, please enter the number of flights in the open field/on the line yourself.

Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 About ___ holiday flights (round-trip flights) a year 1401 68.1% 0.681088965
2 I flew less than once a year 515 25.0% 0.250364609
3 I never flew 130 6.3% 0.063198833
97 Not answered 11 0.5% 0.005347594
98 Not asked 7983 NA


r21km_fly_1_other


Variable label: Open: How often did you travel by air in connection with holiday travel before the Covid-19 pandemic?
Pre-question text: If you think back to before the Covid-19 pandemic, how often would you estimate that you travelled by air in connection with holiday travel?
Literal question: [Open]
Post-question:

If you choose the top option, please enter the number of flights in the open field/on the line yourself.

Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single - Other] [Format:numeric] [Valid:1401] [Invalid:8639] [Range:1-120]

Value Label Cases Percentage
1 324 23.1% 0.2312633833
2 526 37.5% 0.3754461099
3 245 17.5% 0.1748750892
4 159 11.3% 0.1134903640
5 67 4.8% 0.0478229836
6 41 2.9% 0.0292648108
7 5 0.4% 0.0035688794
8 8 0.6% 0.0057102070
9 1 0.1% 0.0007137759
10 16 1.1% 0.0114204140
11 1 0.1% 0.0007137759
12 4 0.3% 0.0028551035
25 2 0.1% 0.0014275517
30 1 0.1% 0.0007137759
120 1 0.1% 0.0007137759
Sysmiss 8639 NA


r21km_fly2


Variable label: Travel more/less by air in connection with holiday travel after the pandemic than before?
Literal question: When the Covid-19 pandemic is over, do you think you will travel by air in connection with holiday travel more often or less frequently than before the pandemic?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Much more frequently 14 0.7% 0.006806028
2 More frequently 38 1.8% 0.018473505
3 A little more frequently 82 4.0% 0.039863879
4 About the same 1365 66.4% 0.663587749
5 A little less frequently 284 13.8% 0.138065143
6 Less frequently 181 8.8% 0.087992222
7 Much less frequently 77 3.7% 0.037433155
97 Not answered 16 0.8% 0.007778318
98 Not asked 7983 NA


r21km_fly4


Variable label: Fits you: Most people I know associate holidays with flights abroad
Pre-question text:

To what extent do you agree with this statement?

Literal question: Most people I know associate holidays with flights abroad.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 To a very large extent 112 5.4% 0.054448226
2 To a large extent 568 27.6% 0.276130287
3 To some extent 906 44.0% 0.440447253
4 To a small extent 394 19.2% 0.191541079
5 Not at all 66 3.2% 0.032085561
97 Not answered 11 0.5% 0.005347594
98 Not asked 7983 NA


r21meme8a_ran


Variable label: Randomly selects alternative for r21meme8a
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2054] [Invalid:7986] [Range:1-5]

Value Label Cases Percentage
1 The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into a hotel run by a multinational commercial company 390 19.0% 0.1898734
2 The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into a mosque. 420 20.4% 0.2044791
3 The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into a mosque. The church spire will be replaced by a minaret. 428 20.8% 0.2083739
4 The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into a mosque. The conversion is being financed by Saudi Arabia. 415 20.2% 0.2020448
5 The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into a mosque. The church spire will be replaced by a minaret. The conversion is being financed by Saudi Arabia. 401 19.5% 0.1952288
Sysmiss 7986 NA


r21meme8a


Variable label: For or against proposal: Sell and convert church into [hotel/mosque]
Pre-question text: The Church of Norway has been debating whether or not to sell some buildings. A proposal has now been made that involves a centrally located church being sold and converted into [a hotel run by a multinational commercial company/a mosque]. [NO MENTION/ the church spire will be replaced by a minaret]. The conversion [NO MENTION/is being financed by Saudi Arabia].
Literal question: Are you in favour of or against the proposal to sell the church?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely in favour 169 8.2% 0.08215848
2 Somewhat in favour 431 21.0% 0.20952844
3 Somewhat against 548 26.6% 0.26640739
4 Completely against 886 43.1% 0.43072436
97 Not answered 23 1.1% 0.01118133
98 Not asked 7983 NA


r21meme9_ran1


Variable label: Experiment. Randomly selects alternative for r21meme9
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2053] [Invalid:7987] [Range:1-2]

Value Label Cases Percentage
1 leaders of Muslim communities 1030 50.2% 0.5017048
2 animal rights activists 1023 49.8% 0.4982952
Sysmiss 7987 NA


r21meme9_ran2


Variable label: Experiment. Randomly selects alternative for r21meme9
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2053] [Invalid:7987] [Range:1-3]

Value Label Cases Percentage
1 if they are suspected of extremism 696 33.9% 0.3390161
2 if they apply for public funding 683 33.3% 0.3326839
3 to safeguard core values of society 674 32.8% 0.3283000
Sysmiss 7987 NA


r21meme9


Variable label: For/against: The Government let PST monitor [Muslim leaders/animal right activists] [if they are suspected of extremism/if they apply for public funding/to safeguard core values of society]
Literal question: Are you for or against the government allowing the Norwegian Police Security Service (PST) to monitor the private lives of [leaders of Muslim communities/animal rights activists] [if they are suspected of extremism/ if they apply for public funding/to safeguard core values of society]?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely in favour 538 26.2% 0.261545941
2 Somewhat in favour 660 32.1% 0.320855615
3 Somewhat against 475 23.1% 0.230918814
4 Completely against 364 17.7% 0.176956733
97 Not answered 20 1.0% 0.009722897
98 Not asked 7983 NA


r21meme12_ran1


Variable label: Experiment. Randomly selects alternative for r21meme12
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2051] [Invalid:7989] [Range:1-3]

Value Label Cases Percentage
1 for Norway to function as it should 718 35.0% 0.3500731
2 to protect core Norwegian values 692 33.7% 0.3373964
3 to help stop global warming 641 31.3% 0.3125305
Sysmiss 7989 NA


r21meme12_ran2


Variable label: Experiment. Randomly selects alternative for r21meme12
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2051] [Invalid:7989] [Range:1-2]

Value Label Cases Percentage
1 [blank] 1052 51.3% 0.5129205
2 – regardless of whether it is legal or not 999 48.7% 0.4870795
Sysmiss 7989 NA


r21meme12


Variable label: Agree/disagree: Must [protect Norwegian values/stop global warming][even if illegal]
Pre-question text: To what extent do you agree or disagree with the following statement:
Literal question: Given what the world looks like today, people have to do what it takes [for Norway to function as it should/to protect core Norwegian values/to help stop global warming] [not mentioned/- regardless of whether it is legal or not].
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely agree 356 17.3% 0.17306757
2 Agree 701 34.1% 0.34078755
3 Disagree 683 33.2% 0.33203695
4 Do not agree at all 271 13.2% 0.13174526
97 Not answered 46 2.2% 0.02236266
98 Not asked 7983 NA


r21meme13_ran1


Variable label: Experiment. Randomly selects alternative for r21meme13
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2048] [Invalid:7992] [Range:1-3]

Value Label Cases Percentage
1 basic human rights 694 33.9% 0.3388672
2 the future of the earth 690 33.7% 0.3369141
3 Norwegian core values 664 32.4% 0.3242188
Sysmiss 7992 NA


r21meme13


Variable label: Agree/disagree: Must work outside of democratic channels when [human rights/values] are at stake
Pre-question text: To what extent do you agree or disagree with the following statement:
Literal question: Sometimes people have to take matters into their own hands instead of using the formal democratic channels when [basic human rights/the future of the earth/Norwegian core values] are at stake.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Completely agree 87 4.2% 0.04229460
2 Agree 496 24.1% 0.24112786
3 Disagree 976 47.4% 0.47447739
4 Do not agree at all 452 22.0% 0.21973748
97 Not answered 46 2.2% 0.02236266
98 Not asked 7983 NA


r21meme14_1


Variable label: Good/bad proposal: Dramatically stricter sentences for criminals
Pre-question text: What is your opinion of the following proposals?
Literal question: Dramatically stricter sentences for criminals
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 373 18.1% 0.18133204
2 Fairly good proposal 609 29.6% 0.29606223
3 Neither a good nor a bad proposal 636 30.9% 0.30918814
4 Fairly bad proposal 319 15.5% 0.15508021
5 Very bad proposal 93 4.5% 0.04521147
97 Not answered 27 1.3% 0.01312591
98 Not asked 7983 NA


r21meme14_2


Variable label: Good/bad proposal: Reduce income inequalities in society
Pre-question text: What is your opinion of the following proposals?
Literal question: Reduce income inequalities in society
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 687 33.4% 0.33398153
2 Fairly good proposal 789 38.4% 0.38356830
3 Neither a good nor a bad proposal 381 18.5% 0.18522120
4 Fairly bad proposal 139 6.8% 0.06757414
5 Very bad proposal 32 1.6% 0.01555664
97 Not answered 29 1.4% 0.01409820
98 Not asked 7983 NA


r21meme14_3


Variable label: Good/bad proposal: Reserve more parental leave days for the father/co-mother
Pre-question text: What is your opinion of the following proposals?
Literal question: Reserve more parental leave days for the father/co-mother
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 119 5.8% 0.05785124
2 Fairly good proposal 393 19.1% 0.19105493
3 Neither a good nor a bad proposal 937 45.6% 0.45551774
4 Fairly bad proposal 383 18.6% 0.18619349
5 Very bad proposal 186 9.0% 0.09042295
97 Not answered 39 1.9% 0.01895965
98 Not asked 7983 NA


r21meme14_4


Variable label: Good/bad proposal: Work to strengthen private entrepreneurship/market economy
Pre-question text: What is your opinion of the following proposals?
Literal question: Work to strengthen private entrepreneurship and the market economy
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 265 12.9% 0.12882839
2 Fairly good proposal 734 35.7% 0.35683034
3 Neither a good nor a bad proposal 697 33.9% 0.33884298
4 Fairly bad proposal 267 13.0% 0.12980068
5 Very bad proposal 63 3.1% 0.03062713
97 Not answered 31 1.5% 0.01507049
98 Not asked 7983 NA


r21meme14_5


Variable label: Good/bad proposal: Make more space for Christian cultural heritage in Norway
Pre-question text: What is your opinion of the following proposals?
Literal question: Make more space for Christian cultural heritage in Norway
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 201 9.8% 0.09771512
2 Fairly good proposal 440 21.4% 0.21390374
3 Neither a good nor a bad proposal 748 36.4% 0.36363636
4 Fairly bad proposal 398 19.3% 0.19348566
5 Very bad proposal 241 11.7% 0.11716091
97 Not answered 29 1.4% 0.01409820
98 Not asked 7983 NA


r21meme14_6


Variable label: Good/bad proposal: Strengthening the State’s control over business and industry
Pre-question text: What is your opinion of the following proposals?
Literal question: Strengthening the State’s control over business and industry
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 119 5.8% 0.05785124
2 Fairly good proposal 532 25.9% 0.25862907
3 Neither a good nor a bad proposal 704 34.2% 0.34224599
4 Fairly bad proposal 519 25.2% 0.25230919
5 Very bad proposal 148 7.2% 0.07194944
97 Not answered 35 1.7% 0.01701507
98 Not asked 7983 NA


r21meme14_7


Variable label: Good/bad proposal: Accept fewer refugees
Pre-question text: What is your opinion of the following proposals?
Literal question: Accept fewer refugees
Technical description:

[Asked if r21group = 5]

[Answer list display order: Randomize]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very good proposal 254 12.3% 0.12348080
2 Fairly good proposal 336 16.3% 0.16334468
3 Neither a good nor a bad proposal 617 30.0% 0.29995139
4 Fairly bad proposal 568 27.6% 0.27613029
5 Very bad proposal 247 12.0% 0.12007778
97 Not answered 35 1.7% 0.01701507
98 Not asked 7983 NA


r21meme15_1


Variable label: Describes you how well: Important to be unprejudiced towards Muslims
Pre-question text: How well or poorly would you say the following descriptions apply to you:
Literal question: It is important for me personally to be unprejudiced towards Muslims.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very well 333 16.2% 0.16188624
2 Well 754 36.7% 0.36655323
3 Somewhat well 401 19.5% 0.19494409
4 Neither well nor poorly 389 18.9% 0.18911035
5 Somewhat poorly 78 3.8% 0.03791930
6 Poorly 40 1.9% 0.01944579
7 Very poorly 34 1.7% 0.01652893
97 Not answered 28 1.4% 0.01361206
98 Not asked 7983 NA


r21meme15_2


Variable label: Describes you how well: Feel guilty if I think negatively about immigrants
Pre-question text: How well or poorly would you say the following descriptions apply to you:
Literal question: I feel guilty if I think negatively about immigrants.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very well 146 7.1% 0.07097715
2 Well 368 17.9% 0.17890131
3 Somewhat well 351 17.1% 0.17063685
4 Neither well nor poorly 643 31.3% 0.31259115
5 Somewhat poorly 207 10.1% 0.10063199
6 Poorly 180 8.8% 0.08750608
7 Very poorly 124 6.0% 0.06028196
97 Not answered 38 1.8% 0.01847351
98 Not asked 7983 NA


r21meme15_3


Variable label: Describes you how well: Try to be unprejudiced towards immigrants because of my own convictions
Pre-question text: How well or poorly would you say the following descriptions apply to you:
Literal question: I try to be unprejudiced towards immigrants because of my own convictions.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very well 295 14.3% 0.14341274
2 Well 697 33.9% 0.33884298
3 Somewhat well 423 20.6% 0.20563928
4 Neither well nor poorly 447 21.7% 0.21730676
5 Somewhat poorly 75 3.6% 0.03646087
6 Poorly 50 2.4% 0.02430724
7 Very poorly 33 1.6% 0.01604278
97 Not answered 37 1.8% 0.01798736
98 Not asked 7983 NA


r21meme15_4


Variable label: Describes you how well: Don’t want to appear racist, not even to myself
Pre-question text: How well or poorly would you say the following descriptions apply to you:
Literal question: I don’t want to appear racist, not even to myself.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very well 479 23.3% 0.23286339
2 Well 679 33.0% 0.33009237
3 Somewhat well 298 14.5% 0.14487117
4 Neither well nor poorly 408 19.8% 0.19834711
5 Somewhat poorly 77 3.7% 0.03743316
6 Poorly 44 2.1% 0.02139037
7 Very poorly 41 2.0% 0.01993194
97 Not answered 31 1.5% 0.01507049
98 Not asked 7983 NA


r21km_oljefremtid_ran


Variable label: Randomly selects whether alternatives in r21km_oljefremtid are shown in reverse order
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2040] [Invalid:8000] [Range:1-2]

Value Label Cases Percentage
1 Normal 1017 49.9% 0.4985294
2 Flipped 1023 50.1% 0.5014706
Sysmiss 8000 NA


r21km_oljefremtid


Variable label: Statement: In 20-30 years, the oil and gas industry should be more/less developed
Pre-question text: Production of oil and gas is an important industry for Norway. The industry provides many jobs and considerable income for society. At the same time, burning fossil energy is the main cause of climate change. Opening new areas is also controversial because it can affect life in the sea and at the ice edge. There are frequent debates about how the oil and gas industry in Norway should be developed over the next 20 to 30 years.
Literal question: Which of the following alternatives is closest to your view?
Post-question: In 20 to 30 years, the industry should be…
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 As developed as possible 88 4.3% 0.043307087
2 More developed than today 79 3.9% 0.038877953
3 As developed as today 503 24.8% 0.247539370
4 Less developed than it is today 839 41.3% 0.412893701
5 As little as possible 516 25.4% 0.253937008
97 7 0.3% 0.003444882
98 8008 NA


r21km_trusselpersonlig


Variable label: How serious a threat is climate change to you personally?
Literal question: How serious a threat is climate change to you personally?
Technical description:

[Asked if r21group = 5]

[Randomised question order with r21km_trusselsamlet.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very serious 190 9.2% 0.09236753
2 Serious 536 26.1% 0.26057365
3 Somewhat serious 649 31.6% 0.31550802
4 Not very serious 458 22.3% 0.22265435
5 Not a threat 194 9.4% 0.09431211
97 Not answered 30 1.5% 0.01458435
98 Not asked 7983 NA


r21km_trusselsamlet


Variable label: How serious a threat is climate change overall?
Literal question: How serious a threat is climate change overall?
Technical description:

[Asked if r21group = 5]

[Randomised question order with r21km_trusselpersonlig.]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 Very serious 723 35.1% 0.35148274
2 Serious 717 34.9% 0.34856587
3 Somewhat serious 411 20.0% 0.19980554
4 Not very serious 112 5.4% 0.05444823
5 Not a threat 63 3.1% 0.03062713
97 Not answered 31 1.5% 0.01507049
98 Not asked 7983 NA


r21km_fly3


Variable label: Can reducing your own flights can help limit climate change?
Literal question: To what extent do you think reducing your own flights can help limit climate change?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 To a very great extent 61 3.0% 0.02965484
2 To a great extent 163 7.9% 0.07924161
3 To some extent 675 32.8% 0.32814779
4 To a small extent 720 35.0% 0.35002431
5 Not at all 405 19.7% 0.19688867
97 Not answered 33 1.6% 0.01604278
98 Not asked 7983 NA


r21km_fly5


Variable label: Agree: Most people I know believe that we should reduce the number of flights
Pre-question text:

To what extent do you agree with this statement?

Literal question: Most people I know believe that we should reduce the number of flights for climate reasons.
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-5]

Value Label Cases Percentage
1 To a very great extent 54 2.6% 0.02625182
2 To a great extent 262 12.7% 0.12736996
3 To some extent 848 41.2% 0.41225085
4 To a small extent 663 32.2% 0.32231405
5 Not at all 190 9.2% 0.09236753
97 Not answered 40 1.9% 0.01944579
98 Not asked 7983 NA


r21km_fly6


Variable label: Does the pandemic make it easier/more difficult to reduce flights for climate reasons in the future?
Pre-question text:

Fewer flights can help limit climate change. During the Covid-19 pandemic, we have had to reduce the number of flights.

Literal question: Do you think this experience from the Covid-19 pandemic may make it easier or more difficult to reduce flights for climate reasons in the future?
Technical description: [Asked if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Very much easier 72 3.5% 0.035002431
2 Much easier 387 18.8% 0.188138065
3 A bit easier 943 45.8% 0.458434614
4 No difference 540 26.3% 0.262518230
5 A bit harder 64 3.1% 0.031113272
6 Much harder 12 0.6% 0.005833738
7 Very much harder 6 0.3% 0.002916869
97 Not answered 33 1.6% 0.016042781
98 Not asked 7983 NA


r21padkom9_ran


Variable label: Randomly selects r21PADKOM9a, r21PADKOM9b or r21PADKOM9c.
Technical description: [Randomized if r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:2032] [Invalid:8008] [Range:1-3]

Value Label Cases Percentage
1 r21PADKOM9a 679 33.4% 0.3341535
2 r21PADKOM9b 688 33.9% 0.3385827
3 r21PADKOM9c 665 32.7% 0.3272638
Sysmiss 8008 NA


r21padkom9a


Variable label: How to redistribute payment that was first determined by lottery?
Pre-question text:

Imagine that two individuals are recruited to do a job, let’s call them Worker A and Worker B. They are told that their payment will be determined by a lottery. The worker who wins the lottery will earn NOK 6,000 for the work, and the other worker will earn nothing.

You will have the opportunity to determine how much each of them receive. The workers will not be told the result of the lottery but will be told that another person will determine their payment for the work.

Imagine that Worker A wins the lottery.

Literal question: Please specify which of the following options would you choose.
Technical description: [Asked if r21padkom9_ran = 1 & r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Worker A would receive NOK 6,000 and Worker B would receive NOK 0 54 8.0% 0.079528719
2 Worker A would receive NOK 5,000 and Worker B would receive NOK 1,000 12 1.8% 0.017673049
3 Worker A would receive NOK 4,000 and Worker B would receive NOK 2,000 42 6.2% 0.061855670
4 Worker A would receive NOK 3,000 and Worker B would receive NOK 3,000 546 80.4% 0.804123711
5 Worker A would receive NOK 2,000 and Worker B would receive NOK 4,000 2 0.3% 0.002945508
6 Worker A would receive NOK 1,000 and Worker B would receive NOK 5,000 1 0.1% 0.001472754
7 Worker A would receive NOK 0 and Worker B would receive NOK 6,000 3 0.4% 0.004418262
97 Not answered 19 2.8% 0.027982327
98 Not asked 9361 NA


r21padkom9b


Variable label: How to redistribute payment that was first determined by productivity?
Pre-question text:

Imagine that two individuals are recruited to do a job, let’s call them Worker A and Worker B. They are told that their payment for their work will be determined by their productivity. The most productive worker will earn NOK 6,000 for the work and the least productive will earn nothing.

You will have the opportunity to determine how much each of them receive. The workers will not be told who was the most productive but will be told that another person will determine their payment for the work.

Imagine that Worker A was the most productive.

You will have the opportunity to determine how much each of them receive. The workers will not be told who was the most productive but will be told that another person will determine their payment for the work.

Imagine that Worker A was the most productive.
Literal question: Please specify which of the following options would you choose.
Technical description: [Asked if r21padkom9_ran = 2 & r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Worker A would receive NOK 6,000 and Worker B would receive NOK 0 39 5.7% 0.056686047
2 Worker A would receive NOK 5,000 and Worker B would receive NOK 1,000 45 6.5% 0.065406977
3 Worker A would receive NOK 4,000 and Worker B would receive NOK 2,000 368 53.5% 0.534883721
4 Worker A would receive NOK 3,000 and Worker B would receive NOK 3,000 216 31.4% 0.313953488
5 Worker A would receive NOK 2,000 and Worker B would receive NOK 4,000 0 0.0% 0.000000000
6 Worker A would receive NOK 1,000 and Worker B would receive NOK 5,000 2 0.3% 0.002906977
7 Worker A would receive NOK 0 and Worker B would receive NOK 6,000 2 0.3% 0.002906977
97 Not answered 16 2.3% 0.023255814
98 Not asked 9352 NA


r21padkom9c


Variable label: How to redistribute lottery-determined payment, when it entails a cost for the lottery’s winner?
Pre-question text:

Imagine that two individuals are recruited to do a job, let’s call them Worker A and Worker B. They are told that their payment will be determined by a lottery. The worker who wins the lottery will earn NOK 6,000 for the work, and the other worker will earn nothing.

You will have the opportunity to determine how much each of them receive, although this will entail a cost. If you choose to redistribute, a NOK 1,000 increase in Worker B’s payment will result in a NOK 2,000 reduction in Worker A’s payment.

The workers will not be told the result of the lottery but will be told that another person will determine their payment for the work.

Imagine that Worker A wins the lottery.

Literal question: Please specify which of the following options would you choose.
Technical description: [Asked if r21padkom9_ran = 3 & r21group = 5]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-4]

Value Label Cases Percentage
1 Worker A would receive NOK 6,000 and Worker B would receive NOK 0 58 8.7% 0.087218045
2 Worker A would receive NOK 4,000 and Worker B would receive NOK 1,000 43 6.5% 0.064661654
3 Worker A would receive NOK 2,000 and Worker B would receive NOK 2,000 540 81.2% 0.812030075
4 Worker A would receive NOK 0 and Worker B would receive NOK 3,000 2 0.3% 0.003007519
97 Not answered 22 3.3% 0.033082707
98 Not asked 9375 NA


r21bktivi_1


Variable label: Resembles me: Respect for parents and elders, obedience
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: [He/She] believes that he should always show respect for his parents and for older people. It’s important to [him/her] to be obedient.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 57 5.2% 0.05219780
5 5 Resembles me 231 21.2% 0.21153846
4 4 Somewhat resembles me 419 38.4% 0.38369963
3 3 Slightly resembles me 211 19.3% 0.19322344
2 2 Does not resemble me 104 9.5% 0.09523810
1 1 Does not resemble me at all 42 3.8% 0.03846154
97 Not answered 28 2.6% 0.02564103
98 Not asked 8948 NA


r21bktivi_2


Variable label: Resembles me: Religion important, fulfills religious requirements
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: Religious faith is important to [him/her]. [He/She] endeavours to do what [his/her] religion requires.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 9 0.8% 0.008241758
5 5 Resembles me 34 3.1% 0.031135531
4 4 Somewhat resembles me 90 8.2% 0.082417582
3 3 Slightly resembles me 150 13.7% 0.137362637
2 2 Does not resemble me 214 19.6% 0.195970696
1 1 Does not resemble me at all 567 51.9% 0.519230769
97 Not answered 28 2.6% 0.025641026
98 Not asked 8948 NA


r21bktivi_3


Variable label: Resembles me: Important to help people, wants to make others do well
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: It’s very important to [him/her] to help the people around him. [He/She] wants to do something to make sure they are doing well.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 179 16.4% 0.1639194139
5 5 Resembles me 423 38.7% 0.3873626374
4 4 Somewhat resembles me 377 34.5% 0.3452380952
3 3 Slightly resembles me 73 6.7% 0.0668498168
2 2 Does not resemble me 9 0.8% 0.0082417582
1 1 Does not resemble me at all 1 0.1% 0.0009157509
97 Not answered 30 2.7% 0.0274725275
98 Not asked 8948 NA


r21bktivi_4


Variable label: Resembles me: Treat people equally, equal opportunities
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: [He/She] thinks it’s important that all people in the world be treated equally. [He/She] thinks everyone should have equal opportunities in life.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 287 26.3% 0.262820513
5 5 Resembles me 399 36.5% 0.365384615
4 4 Somewhat resembles me 299 27.4% 0.273809524
3 3 Slightly resembles me 64 5.9% 0.058608059
2 2 Does not resemble me 13 1.2% 0.011904762
1 1 Does not resemble me at all 2 0.2% 0.001831502
97 Not answered 28 2.6% 0.025641026
98 Not asked 8948 NA


r21bktivi_5


Variable label: Resembles me: Interest important, likes to be curious and understand things
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: [He/She] thinks it’s important to be interested in things. [He/She] likes to be curious and tries to understand all sorts of issues.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 219 20.1% 0.200549451
5 5 Resembles me 365 33.4% 0.334249084
4 4 Somewhat resembles me 358 32.8% 0.327838828
3 3 Slightly resembles me 95 8.7% 0.086996337
2 2 Does not resemble me 25 2.3% 0.022893773
1 1 Does not resemble me at all 2 0.2% 0.001831502
97 Not answered 28 2.6% 0.025641026
98 Not asked 8948 NA


r21bktivi_6


Variable label: Resembles me: Likes risks, looks for new experiences
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: [He/She] likes to take risks. [He/She]’s always looking for new experiences.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 26 2.4% 0.02380952
5 5 Resembles me 86 7.9% 0.07875458
4 4 Somewhat resembles me 256 23.4% 0.23443223
3 3 Slightly resembles me 374 34.2% 0.34249084
2 2 Does not resemble me 223 20.4% 0.20421245
1 1 Does not resemble me at all 97 8.9% 0.08882784
97 Not answered 30 2.7% 0.02747253
98 Not asked 8948 NA


r21bktivi_7


Variable label: Resembles me: Seeks out fun, important to do things that brings pleasure
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: [He/She] seeks out any opportunity to have fun. It is important for him to do things that give him pleasure.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 39 3.6% 0.03571429
5 5 Resembles me 133 12.2% 0.12179487
4 4 Somewhat resembles me 399 36.5% 0.36538462
3 3 Slightly resembles me 335 30.7% 0.30677656
2 2 Does not resemble me 112 10.3% 0.10256410
1 1 Does not resemble me at all 48 4.4% 0.04395604
97 Not answered 26 2.4% 0.02380952
98 Not asked 8948 NA


r21bktivi_8


Variable label: Resembles me: Important to be successful, likes to impress
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: It’s important to [him/her] to be successful. [He/She] likes to impress other people.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 17 1.6% 0.01556777
5 5 Resembles me 97 8.9% 0.08882784
4 4 Somewhat resembles me 276 25.3% 0.25274725
3 3 Slightly resembles me 374 34.2% 0.34249084
2 2 Does not resemble me 195 17.9% 0.17857143
1 1 Does not resemble me at all 105 9.6% 0.09615385
97 Not answered 28 2.6% 0.02564103
98 Not asked 8948 NA


r21bktivi_9


Variable label: Resembles me: Likes to lead, wants others to do as they say
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: It is important for him to take the lead and tell others what to do. He wants people to do as he says.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 6 0.5% 0.005494505
5 5 Resembles me 61 5.6% 0.055860806
4 4 Somewhat resembles me 298 27.3% 0.272893773
3 3 Slightly resembles me 349 32.0% 0.319597070
2 2 Does not resemble me 225 20.6% 0.206043956
1 1 Does not resemble me at all 126 11.5% 0.115384615
97 Not answered 27 2.5% 0.024725275
98 Not asked 8948 NA


r21bktivi_10


Variable label: Resembles me: Tidiness and cleanliness important, doesn’t like mess
Pre-question text: Here we briefly describe some people. Read each description, and think about how much this person resembles you. For each person described, check the form for how much this person resembles or does not resemble you.
Literal question: It’s important to [him/her] that things are tidy and clean. [He/She] really doesn’t like things to be messy.
Technical description:

[Asked if rekruttert = 18]

[Answer list display order: Randomize]

[The person described in the question has the same gender as the respondent.]
Technical attributes: [Question type:Grid] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
6 6 Very much resembles me 141 12.9% 0.12912088
5 5 Resembles me 278 25.5% 0.25457875
4 4 Somewhat resembles me 383 35.1% 0.35073260
3 3 Slightly resembles me 161 14.7% 0.14743590
2 2 Does not resemble me 79 7.2% 0.07234432
1 1 Does not resemble me at all 23 2.1% 0.02106227
97 Not answered 27 2.5% 0.02472527
98 Not asked 8948 NA


r21padkom34


Variable label: Agree/disagree: Tend to exploit others for my own gain
Pre-question text:

To what extent do you agree or disagree with the following statement:

Literal question: I tend to exploit others for my own gain.
Technical description: [Asked if r21group = 3]
Technical attributes: [Question type:Single] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 Strongly agree 4 0.2% 0.002060793
2 Agree 4 0.2% 0.002060793
3 Somewhat agree 47 2.4% 0.024214323
4 Neither agree nor disagree 105 5.4% 0.054095827
5 Somewhat disagree 102 5.3% 0.052550232
6 Disagree 640 33.0% 0.329726945
7 Strongly disagree 995 51.3% 0.512622360
97 Not answered 44 2.3% 0.022668727
98 Not asked 8099 NA


r21avslutt


Variable label: Open: Feedback about the survey
Technical description: [All respondents asked]
Technical attributes: [Question type: -] [Format:character] [Valid:0] [Invalid:10040] [Range:-]



r21P1


Variable label: Gender
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-2]

Value Label Cases Percentage
1 Male 5116 51.0% 0.5095618
2 Female 4924 49.0% 0.4904382


r21P2


Variable label: Region
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-6]

Value Label Cases Percentage
1 Oslo 1602 16.0% 0.15956175
2 Østlandet 3628 36.1% 0.36135458
3 Sørlandet 502 5.0% 0.05000000
4 Vestlandet 2715 27.0% 0.27041833
5 Trøndelag 805 8.0% 0.08017928
6 Nord-Norge 788 7.8% 0.07848606


r21P3


Variable label: County
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:3-54]

Value Label Cases Percentage
3 Oslo 1602 16.0% 0.15956175
11 Rogaland 934 9.3% 0.09302789
15 Møre og Romsdal 412 4.1% 0.04103586
18 Nordland 385 3.8% 0.03834661
30 Viken 2348 23.4% 0.23386454
34 Innlandet 539 5.4% 0.05368526
38 Vestfold og Telemark 741 7.4% 0.07380478
42 Agder 502 5.0% 0.05000000
46 Vestland 1369 13.6% 0.13635458
50 Trøndelag 805 8.0% 0.08017928
54 Troms og Finnmark 403 4.0% 0.04013944


r21P3_2


Variable label: Constituencies parliament election 2021
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-19]

Value Label Cases Percentage
3 Østfold 475 4.7% 0.04731076
1 Akershus 1407 14.0% 0.14013944
2 Oslo 1602 16.0% 0.15956175
5 Hedmark 299 3.0% 0.02978088
6 Oppland 240 2.4% 0.02390438
7 Buskerud 466 4.6% 0.04641434
4 Vestfold 473 4.7% 0.04711155
8 Telemark 268 2.7% 0.02669323
10 Aust-Agder 178 1.8% 0.01772908
9 Vest-Agder 324 3.2% 0.03227092
11 Rogaland 934 9.3% 0.09302789
12 Hordaland 1209 12.0% 0.12041833
13 Sogn og Fjordane 160 1.6% 0.01593625
14 Møre og Romsdal 412 4.1% 0.04103586
16 Sør-Trøndelag 639 6.4% 0.06364542
15 Nord-Trøndelag 166 1.7% 0.01653386
17 Nordland 385 3.8% 0.03834661
18 Troms 300 3.0% 0.02988048
19 Finnmark 103 1.0% 0.01025896


r21P4_1


Variable label: Highest completed education
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 No education/elementary school 470 4.7% 0.04681275
2 Upper secondary education 3016 30.0% 0.30039841
3 University/University college 6386 63.6% 0.63605578
97 Not answered 168 1.7% 0.01673307


r21P4_2


Variable label: Highest completed education
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-12]

Value Label Cases Percentage
1 No completed education 22 0.2% 0.002191235
2 Primary and lower secondary school (completed either the first part of compulsory education (elementary school), primary and lower secondary school, 7-year elementary school, secondary modern school or lower secondary school) 448 4.5% 0.044621514
3 Secondary education-general studies/programme for general studies, one-year supplementary study for university and college admission certification (VK2, VG3, High School) 907 9.0% 0.090338645
4 Secondary education-vocational line of study/education programme (VK2, VK3, VG3, apprenticeship examination, apprentices’ final exam ) 1179 11.7% 0.117430279
5 Diploma from supplementary programme for general university and college admissions certification (tertiary vocational education, vocational technical college) 927 9.2% 0.092330677
6 University/College, less than 3 years, but at least 2 years (university college graduate 2 and 2½ years) 837 8.3% 0.083366534
7 College-3-4 year education (Bachelor-, cand.mag., teacher training college, school of nursing, preschool teacher, engineer, business graduate, etc.) 2121 21.1% 0.211254980
8 University-3-4 year education (Bachelor, cand.mag.) 720 7.2% 0.071713147
9 College-5-6 year education (Master, major) 742 7.4% 0.073904382
10 University 5-6 year education (Master, majors (longer professional education (MA in Theology., MA in Psychology., Doctor of Medicine, Doctor of Veterinary Medicine, chartered engineer, graduate in architecture, Master of Science in Business and Economic 1694 16.9% 0.168725100
11 Researcher level (Doctorate, Ph.d.) 272 2.7% 0.027091633
12 None of the above (please enter): 134 1.3% 0.013346614
97 Not answered 37 0.4% 0.003685259


r21P5_1


Variable label: Year of birth
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-7]

Value Label Cases Percentage
1 1939 or earlier 261 2.6% 0.02599602
2 1940-1949 1712 17.1% 0.17051793
3 1950-1959 2554 25.4% 0.25438247
4 1960-1969 2251 22.4% 0.22420319
5 1970-1979 1517 15.1% 0.15109562
6 1980-1989 1026 10.2% 0.10219124
7 1990 or later 719 7.2% 0.07161355


r21P5_2


Variable label: Year of birth
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:1-3]

Value Label Cases Percentage
1 1959 or earlier 4527 45.1% 0.45089641
2 1960-1989 4794 47.7% 0.47749004
3 1990 or later 719 7.2% 0.07161355


r21Weight1_stratapop


Variable label: Indicates the proportion size of strata in the population. Strata constructed with P1, P2, and age
Technical description: [Can be used for calculating custom weights. Please see documentation report.]
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-0]



r21Weight1


Variable label: Weight based on variables P1, P2, and age. See documentation report.
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-6]



r21Weight2_stratapop


Variable label: Indicates the proportion size of strata in the population. Strata constructed with P1, P2, P4_1, and age
Technical description: [Can be used for calculating custom weights. Please see documentation report.]
Technical attributes: [Question type: -] [Format:numeric] [Valid:9872] [Invalid:168] [Range:0-0]



r21Weight2


Variable label: Weight based on variables P1, P2, P4_1, and age. See documentation report.
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-66]



r21Weight4


Variable label: Weight based on variables P1, P2, P4_1 (Note! recoded to two-level: 1) upper secondary and lower, and 2) University/University college), and age. Similiar to Weight2 only with capped weight value (x is >= .2 and x <= 5).
Technical attributes: [Question type: -] [Format:numeric] [Valid:10040] [Invalid:0] [Range:0-5]