kim_2024_class_gender_us

5,136 rated or chosen profiles from 865 respondents, in up to 3 tasks of 2 profiles varying on 5 attributes.

One of 2 tables from the same source; this one is the us table. The others are listed under Related tables.

About this table

DescriptionUS respondents (Lucid online sample, October 2021, n=865) chose between two hypothetical candidates in their party's congressional primary in 3 tasks, varying gender, age, education, former occupation (working-class vs white-collar) and years in politics; 15 forced-choice questions per pair (support, relatability, which better represents five groups, which better advocates on seven issues and on the respondent's top issue).
ReferenceKim, J. H., & Kweon, Y. (2024). Double penalty? How candidate class and gender influence voter evaluations. Research & Politics, 11(1).
DOI10.1177/20531680241226511
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/EWQKH3

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

Respondents865
Rows (one per respondent, task and profile)5,136
Tasks per respondent (most)3
Profiles per task2
Attributes5
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryUS
Language shownen
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceBased on the profiles above, which of the two candidates would you be more likely to support in this [Democratic/Republican] Party's congressional primary? [choice, forced]
choice_advocate_economyBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Economy [choice, forced]
choice_advocate_educationBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Education [choice, forced]
choice_advocate_familyBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Child/ Family [choice, forced]
choice_advocate_gender_equalityBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Gender Equality [choice, forced]
choice_advocate_healthBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Health [choice, forced]
choice_advocate_racial_equalityBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Racial Equality [choice, forced]
choice_advocate_welfareBased on the profiles above, which of the two candidates do you think will do a better job advocating for the following issues? - Social Welfare [choice, forced]
choice_relateBased on the profiles above, which of the two candidates can you relate to more? [choice, forced]
choice_represent_immigrantsBased on the profiles above, which of the two candidates do you think will better represent the following constituents? - Immigrants [choice, forced]
choice_represent_low_incomeBased on the profiles above, which of the two candidates do you think will better represent the following constituents? - Low income group [choice, forced]
choice_represent_minoritiesBased on the profiles above, which of the two candidates do you think will better represent the following constituents? - Racial minorities [choice, forced]
choice_represent_whitesBased on the profiles above, which of the two candidates do you think will better represent the following constituents? - Whites [choice, forced]
choice_represent_womenBased on the profiles above, which of the two candidates do you think will better represent the following constituents? - Women [choice, forced]
choice_top_issueYou chose [most important issue] as the most important policy issue to you. Based on the profiles above, which of the two candidates do you think will do a better job advocating for that issue? [choice, forced]

Columns

attr_ageattr_educationattr_genderattr_occupationattr_years_in_politicsattrpos_ageattrpos_educationattrpos_genderattrpos_occupationattrpos_years_in_politicschoicechoice_advocate_economychoice_advocate_educationchoice_advocate_familychoice_advocate_gender_equalitychoice_advocate_healthchoice_advocate_racial_equalitychoice_advocate_welfarechoice_relatechoice_represent_immigrantschoice_represent_low_incomechoice_represent_minoritieschoice_represent_whiteschoice_represent_womenchoice_top_issuecov_agecov_educationcov_gender_codecov_interestcov_party_id_codecov_party_lean_codecov_top_issue_codeidprofiletasktrial_primary

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("kim_2024_class_gender_us", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("kim_2024_class_gender_us", source="conj")

How to cite

@article{Kim_2024, title={Double penalty? How candidate class and gender influence voter evaluations}, volume={11}, ISSN={2053-1680}, url={http://dx.doi.org/10.1177/20531680241226511}, DOI={10.1177/20531680241226511}, number={1}, journal={Research &amp; Politics}, publisher={SAGE Publications}, author={Kim, Jeong Hyun and Kweon, Yesola}, year={2024}, month=Jan }

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