1,490 rated or chosen profiles from 1,490 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.
| Description | Respondents to a 2014 CCES team module (n = 1,490 with an answer) each rated one text description of a hypothetical congressional candidate whose name (David / Denise Jones) and stated income ($75,000, $3 million, or none) were randomized; outcomes are vote likelihood (1-4) and five trait ratings. |
|---|---|
| Reference | Griffin, J. D., Newman, B., & Buhr, P. (2020). Class war in the voting booth: Bias against high-income congressional candidates. Legislative Studies Quarterly, 45(1), 131-145. |
| DOI | 10.1111/lsq.12253 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/U5B81D |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,490 |
|---|---|
| Rows (one per respondent, task and profile) | 1,490 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 2 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | inferred from row order |
| Profile position | inferred from row order |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating | Vote for candidate (paraphrase) [rating, 1 (I would definitely not vote for this candidate) to 4 (I would definitely vote for this candidate)] |
|---|---|
| rating_cares | How well does 'cares about people like you' describe the candidate (paraphrase) [rating, 1 (Extremely well) to 5 (Not well at all)] |
| rating_honest | How well does 'honest' describe the candidate (paraphrase) [rating, 1 (Extremely well) to 5 (Not well at all)] |
| rating_intelligent | How well does 'intelligent' describe the candidate (paraphrase) [rating, 1 (Extremely well) to 5 (Not well at all)] |
| rating_leadership | How well does 'provide strong leadership' describe the candidate (paraphrase) [rating, 1 (Extremely well) to 5 (Not well at all)] |
| rating_represent | How well would the candidate represent you in office (paraphrase) [rating, 1 (Very well) to 4 (Very poorly)] |
attr_incomeattr_namecov_millionairescov_perceived_partycov_survey_weightidprofileratingrating_caresrating_honestrating_intelligentrating_leadershiprating_representtask
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("griffin_2020_candidate_income", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("griffin_2020_candidate_income", source="conj")
@article{Griffin_2019, title={Class War in the Voting Booth: Bias Against High‐Income Congressional Candidates}, volume={45}, ISSN={1939-9162}, url={http://dx.doi.org/10.1111/lsq.12253}, DOI={10.1111/lsq.12253}, number={1}, journal={Legislative Studies Quarterly}, publisher={Wiley}, author={Griffin, John D. and Newman, Brian and Buhr, Patrick}, year={2019}, month=Sept, pages={131–145} }
| 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 |