22,096 rated or chosen profiles from 11,048 respondents, in up to 1 tasks of 2 profiles varying on 2 attributes.
One of 2 tables from the same source; this one is the 2018 table. The others are listed under Related tables.
| Description | Republican caucus attenders (n = 11,048) chose between a woman (Julie Baker) and a man (Steven Hall) candidate for state delegate after reading each one's self-description; each candidate's self-presentation (Masculine, Masculine+Parent, Feminine, Feminine+Parent) was independently randomized (4 x 4); outcomes are the vote and likeable/competent ratings. |
|---|---|
| Reference | Karpowitz, C. F., Monson, J. Q., Preece, J. R., & Aldridge, A. (2023). Selecting for masculinity: Women's under-representation in the Republican Party. American Political Science Review. |
| DOI | 10.1017/S0003055423000783 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/Z0IGLS |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 11,048 |
|---|---|
| Rows (one per respondent, task and profile) | 22,096 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 2 |
| Attributes | 2 |
| Tasks with no profile chosen | 0 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | unknown |
Outcomes:
| choice | If these two candidates were running for state delegate in your precinct this year, who would you vote for? Julie Baker / Steven Hall [choice, forced] |
|---|---|
| rating_competent | Following is a list of words and phrases people may use to describe political figures. In your opinion, how well do these words and phrases describe [candidate]? Competent [rating, 1 (Not well at all) to 4 (Extremely well)] |
| rating_likeable | Following is a list of words and phrases people may use to describe political figures. In your opinion, how well do these words and phrases describe [candidate]? Likeable [rating, 1 (Not well at all) to 4 (Extremely well)] |
attr_candidateattr_profile_typechoicecov_agecov_educationcov_gendercov_income_codecov_marriedcov_nonwhitecov_religiositycov_strong_conservativeidprofilerating_competentrating_likeabletask
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("karpowitz_2023_masculinity_2018", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("karpowitz_2023_masculinity_2018", source="conj")
@article{KARPOWITZ_2024, title={Selecting for Masculinity: Women’s Under-Representation in the Republican Party}, volume={118}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/S0003055423000783}, DOI={10.1017/s0003055423000783}, number={4}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={KARPOWITZ, CHRISTOPHER F. and MONSON, J. QUIN and PREECE, JESSICA R. and ALDRIDGE, ALEJANDRA}, year={2024}, month=Jan, pages={1873–1894} }
| 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 |