3,000 rated or chosen profiles from 3,000 respondents, in up to 1 tasks of 1 profile varying on 3 attributes.
| Description | Japanese online-panel respondents (Rakuten Insight, March 2024, n = 3,000) each read one vignette about a hypothetical LDP candidate randomized by name (Japanese, American or Chinese), origin (Japan, U.S., China) and migrant-voting-rights policy (pro or restrictive), and rated willingness to vote for and favorability toward the candidate (5-point). |
|---|---|
| Reference | Igarashi, A., & Ono, Y. (2025). Voter preferences for ethnoracial minority candidates: The role of policy alignment and shared identity. Journal of Experimental Political Science. |
| DOI | 10.1017/XPS.2025.1 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/Z518MY |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 3,000 |
|---|---|
| Rows (one per respondent, task and profile) | 3,000 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 3 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | JP |
| Language shown | ja |
| Language of stored levels | ja |
| Randomization restrictions | yes (stated by the source): a Japanese-origin candidate always has the Japanese name; an American-origin candidate has the Japanese or the American name; a Chinese-origin candidate has the Japanese or the Chinese name (article Research Design; nameorigin in replication.do; checked in the data: 3 of the 9 name-by-origin cells are empty) |
| Task order | inferred from row order |
| Profile position | inferred from row order |
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. Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating_favorability | favorability toward the candidate (5-point; wording and labels not in deposit; raw 1 = most favourable, inferred from the authors' recode 6 - Q13.4) [rating, 1 (most favourable (raw 1, inferred)) to 5 (least favourable (raw 5, inferred))] |
|---|---|
| rating_vote_willingness | likelihood of voting for the candidate (5-point; wording and labels not in deposit; raw 1 = most willing, inferred from the authors' recode 6 - Q13.5) [rating, 1 (most willing to vote (raw 1, inferred)) to 5 (least willing to vote (raw 5, inferred))] |
attr_candidate_nameattr_candidate_originattr_candidate_policycov_agecov_attention_passcov_education_codecov_gender_codeidprofilerating_favorabilityrating_vote_willingnesstask
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.
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("igarashi_2025_minority_candidates", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("igarashi_2025_minority_candidates", source="conj")
@article{Igarashi_2025, title={Voter Preferences for Ethnoracial Minority Candidates: The Role of Policy Alignment and Shared Identity}, volume={13}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/XPS.2025.1}, DOI={10.1017/xps.2025.1}, number={2}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Igarashi, Akira and Ono, Yoshikuni}, year={2025}, month=Feb, pages={217–231} }
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint_2 v1.4 |
| Redivis dataset DOI | 10.57761/hk97-wv30 |
| Manifest pin for this IRW version | v1.4 |
| Metadata source | irw_meta v44.0 |