blumenau_2024_representation_de

30,488 rated or chosen profiles from 3,050 respondents, in up to 5 tasks of 2 profiles varying on 8 attributes.

One of 3 tables from the same source; this one is the de table. The others are listed under Related tables.

About this table

DescriptionOnline quota-sample respondents in Germany (Lucid, May-September 2021; n = 3,050 who reached the conjoint) each read 5 pairs of text descriptions of politicians (gender plus one further social characteristic, party and constituency link, justification style, a responsiveness quote, party-vs-own voting, and a stance on one policy issue) and chose who would better represent them. Outcome: forced choice.
ReferenceBlumenau, J., Wolkenstein, F., & Wratil, C. (2024). Citizens' preferences for multidimensional representation. Perspectives on Politics, 23(2), 588-610.
DOI10.1017/S1537592724001373
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/EZDPNP

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents3,050
Rows (one per respondent, task and profile)30,488
Tasks per respondent (most)5
Profiles per task2
Attributes8
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryDE
Language shownde
Language of stored levelsde
Randomization restrictionsyes (stated by the source): one policy issue per pair (same issue for both politicians, stance varies); the descriptive sentence shows gender plus ONE of ethnicity/sexuality/class, the same characteristic type for both politicians of a pair (plumber_de.R desc_chars_in_task); probabilities: ethnicity no migration background .8 (shown as nothing: '(not shown)'), Turkish/Polish/Russian .2/3 each; sexuality heterosexual .9 / homosexual .1; others uniform. Party: CDU/CSU, SPD, Bündnis 90/Grüne; five mandate phrases
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead.

Outcomes:

choiceWelcher dieser Politiker würde Sie ihrer Meinung nach besser in der Politik vertreten? [choice, forced]

Columns

attr_characteristicattr_genderattr_justificationattr_mandateattr_partyattr_personalizationattr_responsivenessattr_substantiveattrpos_characteristicattrpos_genderattrpos_justificationattrpos_mandateattrpos_partyattrpos_personalizationattrpos_responsivenessattrpos_substantivechoicecov_attention_passcov_birth_yearcov_classcov_duration_seccov_educationcov_gendercov_ideologycov_migration_backgroundcov_regioncov_sexualitycov_vote_lastidprofiletask

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("blumenau_2024_representation_de", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("blumenau_2024_representation_de", source="conj")

How to cite

@article{Blumenau_2024, title={Citizens’ Preferences for Multidimensional Representation}, volume={23}, ISSN={1541-0986}, url={http://dx.doi.org/10.1017/S1537592724001373}, DOI={10.1017/s1537592724001373}, number={2}, journal={Perspectives on Politics}, publisher={Cambridge University Press (CUP)}, author={Blumenau, Jack and Wolkenstein, Fabio and Wratil, Christopher}, year={2024}, month=Dec, pages={588–610} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0