45,340 rated or chosen profiles from 2,267 respondents, in up to 20 tasks of 1 profile varying on 8 attributes.
| Description | Japanese voters (Rakuten Insight online panel, July 2020, n=2,267) rated 20 hypothetical Diet candidates one at a time on an 8-point favorability scale, 10 for the House of Representatives and 10 for the House of Councillors (chamber order randomized; half primed on the lower house's power to elect the PM); 8 attributes with real-world level probabilities (gender, party, age, education, occupation, hometown, experience, dynasty). |
|---|---|
| Reference | Ono, Y., Kasuya, Y., & Miwa, H. (2025). Analyzing gender gaps in bicameral legislatures: How asymmetrical institutions affect the supply and demand for female candidates. Legislative Studies Quarterly, 50(3), e12493. |
| DOI | 10.1111/lsq.12493 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/8SX9CK |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,267 |
|---|---|
| Rows (one per respondent, task and profile) | 45,340 |
| Tasks per respondent (most) | 20 |
| Profiles per task | 1 |
| Attributes | 8 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | JP |
| Language shown | ja |
| Language of stored levels | ja |
| Randomization restrictions | unknown |
| Task order | inferred from row order |
| Profile position | recorded in the deposit |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating | To what extent is this candidate favorable as a [HoR/HoC] member? Please evaluate this candidate using an eight-point scale from "not favorable at all" to "very favorable." (translated) [rating, 1 (not favorable at all) to 8 (very favorable)] |
|---|
attr_ageattr_dynastyattr_educationattr_experienceattr_genderattr_hometownattr_occupationattr_partyattrpos_ageattrpos_dynastyattrpos_educationattrpos_experienceattrpos_genderattrpos_hometownattrpos_occupationattrpos_partycov_agecov_educationcov_gendercov_importance_hoccov_importance_horcov_importance_localcov_party_idcov_prefectureidprofileratingtasktrial_chambertrial_priming
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("ono_2025_bicameral_gender", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("ono_2025_bicameral_gender", source="conj")
@article{Ono_2025, title={Analyzing gender gaps in bicameral legislatures: How asymmetrical institutions affect the supply and demand for female candidates}, volume={50}, ISSN={1939-9162}, url={http://dx.doi.org/10.1111/lsq.12493}, DOI={10.1111/lsq.12493}, number={3}, journal={Legislative Studies Quarterly}, publisher={Wiley}, author={Ono, Yoshikuni and Kasuya, Yuko and Miwa, Hirofumi}, year={2025}, month=Mar }
| 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 |