16,427 rated or chosen profiles from 16,427 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.
| Description | Respondents in 12 democracies read one news vignette about a newly elected municipal council (all men, gender-balanced, or gender-balanced under a quota rule) that adopted a policy on sexual harassment or animal mistreatment, then rated the decision's substantive and procedural legitimacy on 1-4 scales. n = 16,427 across ten survey files. |
|---|---|
| Reference | Clayton, A., O'Brien, D. Z., & Piscopo, J. M. (2025). Electoral gender quotas and democratic legitimacy. American Political Science Review. |
| DOI | 10.1017/S0003055425000176 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/D67GRI |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 16,427 |
|---|---|
| Rows (one per respondent, task and profile) | 16,427 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 2 |
| Topic | democracy institutions |
|---|---|
| A profile represents | scenario |
| Country | AR, AU, BR, FR, MX, NZ, NO, PE, PT, ES, GB, US |
| Language shown | es, pt, en |
| Language of stored levels | en |
| Randomization restrictions | yes (stated by the source): the animal-mistreatment issue was not fielded in Australia, France and Norway (harassment vignettes only; authors' processing script note), so the issue is not crossed with composition there |
| 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_fair_process | Thinking for a moment about the gender composition of the council, how fair was the decision-making process? [rating, 1 (very unfair) to 4 (very fair)] |
|---|---|
| rating_fair_target | How fair was this decision to women / for the treatment of animals? [rating, 1 (very unfair) to 4 (very fair)] |
| rating_overturn | Please tell us if you agree: The council's decision should be overturned. (stored raw; higher = more agreement that it should be overturned) [rating, 1 (strongly disagree) to 4 (strongly agree)] |
| rating_right_citizens | Please tell us if you agree: The council made the right decision for all local citizens. [rating, 1 (strongly disagree) to 4 (strongly agree)] |
| rating_right_target | Please tell us if you agree: The council made the right decision for women (sexual harassment vignettes) / the treatment of animals (animal vignettes). [rating, 1 (strongly disagree) to 4 (strongly agree)] |
| rating_trust | Please tell us if you agree: The council can be trusted to make decisions that are right for local citizens. [rating, 1 (strongly disagree) to 4 (strongly agree)] |
attr_council_compositionattr_policy_issuecov_agecov_age_groupcov_countrycov_duration_seccov_gendercov_manipulation_passcov_module_seccov_survey_weightidprofilerating_fair_processrating_fair_targetrating_overturnrating_right_citizensrating_right_targetrating_trusttask
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("clayton_2025_gender_quotas", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("clayton_2025_gender_quotas", source="conj")
@article{CLAYTON_2025, title={Electoral Gender Quotas and Democratic Legitimacy}, volume={120}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/S0003055425000176}, DOI={10.1017/s0003055425000176}, number={1}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={CLAYTON, AMANDA and O’BRIEN, DIANA Z. and PISCOPO, JENNIFER M.}, year={2025}, month=Apr, pages={123–140} }
| 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 |