938 rated or chosen profiles from 469 respondents, in up to 1 tasks of 2 profiles varying on 8 attributes.
One of 4 tables from the same source; this one is the lucid1 table. The others are listed under Related tables.
| Description | Democratic congressional primary candidate conjoint (Lucid study 1): 469 white Democrats (Lucid, 2022) each chose between one Black and one White hypothetical candidate differing in race, age, job, political experience, endorsement and positions on healthcare, fossil fuels and reparations. Outcomes: vote choice plus eight 0-1 ratings of each candidate (favourability, perceived ideology, six trait descriptions). |
|---|---|
| Reference | Mikkelborg, A. C. (2025). White Democrats' growing support for Black politicians in the era of the "Great Awokening." American Political Science Review. |
| DOI | 10.1017/S0003055425000097 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/LMBY8P |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 469 |
|---|---|
| Rows (one per respondent, task and profile) | 938 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 2 |
| Attributes | 8 |
| 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 | yes (stated by the source): race: one candidate always Black and the other White; the two candidates never share an endorsement (appendix also: nor the same priority if elected); other attributes equal probability |
| Task order | inferred from row order |
| Profile position | recorded in the deposit |
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:
| choice | Which candidate for Congress would you support in this Democratic Primary election? [choice, forced] |
|---|---|
| rating_demvotes | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Would perform well with loyal Democratic voters [rating, 0 (Not well at all) to 1 (Extremely well)] |
| rating_favor | Do you have a favorable or unfavorable opinion of [CANDIDATE A/CANDIDATE B]? [rating, 0 (Very unfavorable) to 1 (Very favorable)] |
| rating_goodchance | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Has a good chance of winning the general election [rating, 0 (Not well at all) to 1 (Extremely well)] |
| rating_goodjob | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Would do a good job if elected [rating, 0 (Not well at all) to 1 (Extremely well)] |
| rating_ideology | If you had to guess, how would you describe [CANDIDATE A'S/CANDIDATE B'S] political views in general? [rating, 0 (Very liberal) to 1 (Strongly conservative)] |
| rating_repsgroups | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Represents historically underrepresented groups [rating, 0 (Not well at all) to 1 (Extremely well)] |
| rating_repsme | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Represents people like me [rating, 0 (Not well at all) to 1 (Extremely well)] |
| rating_swingvotes | Please indicate how well you feel each phrase describes [CANDIDATE A/CANDIDATE B]: Would perform well with swing voters [rating, 0 (Not well at all) to 1 (Extremely well)] |
attr_ageattr_climateattr_endorsementattr_experienceattr_healthcareattr_jobattr_raceattr_reparationschoicecov_age01cov_educationcov_gendercov_hhinccov_regioncov_strength_demidprofilerating_demvotesrating_favorrating_goodchancerating_goodjobrating_ideologyrating_repsgroupsrating_repsmerating_swingvotestask
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("mikkelborg_2025_primary_lucid1", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("mikkelborg_2025_primary_lucid1", source="conj")
@article{MIKKELBORG_2025, title={White Democrats’ Growing Support for Black Politicians in the Era of the “Great Awokening”}, volume={119}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/S0003055425000097}, DOI={10.1017/s0003055425000097}, number={4}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={MIKKELBORG, ANNA CAROLINE}, year={2025}, month=Feb, pages={1902–1920} }
| 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 |