24,000 rated or chosen profiles from 3,000 respondents, in up to 8 tasks of 1 profile varying on 7 attributes.
| Description | 3,000 news-engaged US registered voters (YouGov, January 2024) each read 8 text descriptions of a city-council seat varying 7 features (campaign funds needed, chances of winning, salary, local news exposure, majority needed to pass policy, city manager powers, staff) and rated their interest in running for it on a 1-10 scale. |
|---|---|
| Reference | Eggers, A., Fowler, A., Howell, W., & Offer-Westort, M. (2025). Opportunities to govern: How to increase the supply of moderate and qualified candidates. Political Science Research and Methods. |
| DOI | 10.1017/psrm.2025.10076 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/BQAHGZ |
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) | 24,000 |
| Tasks per respondent (most) | 8 |
| Profiles per task | 1 |
| Attributes | 7 |
| Topic | democracy institutions |
|---|---|
| A profile represents | product service |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| rating | Interest in running for the city-council office described in the vignette (paraphrase) [rating, 1 (No interest whatsoever) to 10 (Highest possible interest)] |
|---|
attr_city_managerattr_fundraisingattr_local_newsattr_majorityattr_salaryattr_staffattr_winningattrpos_city_managerattrpos_fundraisingattrpos_local_newsattrpos_majorityattrpos_salaryattrpos_staffattrpos_winningcov_agecov_duration_seccov_educationcov_gendercov_ideology7cov_party_idcov_party_id7cov_racecov_statecov_survey_weightidprofileratingtask
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("eggers_2025_council_office", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("eggers_2025_council_office", source="conj")
@article{Eggers_2025, title={Opportunities to govern: how to increase the supply of moderate and qualified candidates}, ISSN={2049-8489}, url={http://dx.doi.org/10.1017/psrm.2025.10076}, DOI={10.1017/psrm.2025.10076}, journal={Political Science Research and Methods}, publisher={Cambridge University Press (CUP)}, author={Eggers, Andrew and Fowler, Anthony and Howell, William and Offer-Westort, Molly}, year={2025}, month=Dec, pages={1–20} }
| 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 |