28,386 rated or chosen profiles from 2,141 respondents, in up to 7 tasks of 2 profiles varying on 4 attributes.
| Description | Candidates in the 2021 Danish municipal elections (n=2,141; 1,939 in the authors' completed-in-time sample) made 7 forced choices between two hypothetical council positions varying in position/influence, remuneration, workload and working environment (respect vs harassment vs sexism). |
|---|---|
| Reference | Kjøller, F. K., & Pedersen, L. H. (2025). The gendered cost of politics. British Journal of Political Science, 55, e59. |
| DOI | 10.1017/S0007123424000310 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/SOLAAJ |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,141 |
|---|---|
| Rows (one per respondent, task and profile) | 28,386 |
| Tasks per respondent (most) | 7 |
| Profiles per task | 2 |
| Attributes | 4 |
| Tasks with no profile chosen | 0 |
| Topic | democracy institutions |
|---|---|
| A profile represents | product service |
| Country | DK |
| Language shown | da |
| Language of stored levels | da |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Forestil dig, at du tilbydes følgende to poster som medlem af byrådet. Sæt dig venligst godt ind i de to poster. Hvilken post vil du vælge? [choice, forced] |
|---|
attr_environmentattr_positionattr_remunerationattr_workloadattrpos_environmentattrpos_positionattrpos_remunerationattrpos_workloadchoicecov_birth_yearcov_educationcov_elected_2021cov_gendercov_harassed_1cov_harassed_2cov_harassed_3cov_harassed_4cov_harassed_5cov_harassment_riskcov_in_authors_samplecov_left_rightcov_maritalcov_political_hourscov_survey_statusidprofiletask
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("kjoller_2025_council_positions", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("kjoller_2025_council_positions", source="conj")
@article{Kj_ller_2025, title={The Gendered Cost of Politics}, volume={55}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123424000310}, DOI={10.1017/s0007123424000310}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Kjøller, Frederik Klaaborg and Pedersen, Lene Holm}, year={2025} }
| 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 |