15,366 rated or chosen profiles from 2,578 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 status table. The others are listed under Related tables.

About this table

Description	Japanese adults (Rakuten Insight panel follow-up survey; n=2,578) chose between two hypothetical male candidates (surname, local/non-local/elite biography, party, years in job), 3 pairs each, for vote choice and for which would act more on six policy issues and on their prefecture's issues.
Reference	Gagnon, E., Ikeda, F., & McElwain, K. M. (2025). Preferring national elites or local candidates: A conjoint analysis of voter heuristics. Journal of Politics.
DOI	10.1086/737779
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/E4OOYT

Notes

Conjoint table (irw_conjoint). choice = vote (forced, Candidate A/B); choice_<issue> = which candidate would act more actively on business attraction, tourism, public works, government debt, diplomacy, pensions; choice_prefecture_issues = which would act more on the respondent's prefecture's issues. attr_local_status is the biography sentence as shown, with the respondent's own prefecture and universities filled in from the export's embedded fields (three designed versions: local, non-local, elite). Candidate gender fixed (male). 2 respondents without embedded values dropped.

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

Design

Topic	candidate choice
A profile represents	person
Country	JP
Language shown	ja
Language of stored levels	ja
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which candidate would you prefer to vote for? Even if there is no candidate you want to choose, please select one candidate you would prefer if you were forced to. (translated) [choice, forced]
choice_business_attraction	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Business attraction (translated) [choice, forced]
choice_diplomacy	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Diplomacy (translated) [choice, forced]
choice_government_debt	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Government debt (translated) [choice, forced]
choice_pensions	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Pensions (translated) [choice, forced]
choice_prefecture_issues	Which candidate do you think will take a more active role in addressing the political issues in your prefecture? (translated) [choice, forced]
choice_public_works	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Public works (translated) [choice, forced]
choice_tourism	Which candidate do you think will take a more active role in addressing the following policy issues? Please consider each issue separately and answer. - Tourism promotion (translated) [choice, forced]

Columns

attr_first_nameattr_last_nameattr_local_statusattr_partyattr_time_on_jobchoicechoice_business_attractionchoice_diplomacychoice_government_debtchoice_pensionschoice_prefecture_issueschoice_public_workschoice_tourismcov_birth_yearcov_city_sizecov_duration_seccov_educationcov_finishedcov_gendercov_party_idcov_prefectureidprofiletask

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 needed Browse on Redivisexplore and query Croissant 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("gagnon_2025_local_status", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("gagnon_2025_local_status", source="conj")

How to cite

@article{Gagnon_2025, title={Preferring National Elites or Local Candidates: A Conjoint Analysis of Voter Heuristics}, ISSN={1468-2508}, url={http://dx.doi.org/10.1086/737779}, DOI={10.1086/737779}, journal={The Journal of Politics}, publisher={University of Chicago Press}, author={Gagnon, Etienne and Ikeda, Fumi and McElwain, Kenneth Mori}, year={2025}, month=July, pages={000–000} }

Respondents	2,578
Rows (one per respondent, task and profile)	15,366
Tasks per respondent (most)	3
Profiles per task	2
Attributes	5
Tasks with no profile chosen	0

IRW version	v584
Redivis dataset	irw_conjoint v4.2
Redivis dataset DOI	10.57761/qkye-q530
Manifest pin for this IRW version	v4.2
Metadata source	irw_meta v44.0

gagnon_2025_local_status