56,655 rated or chosen profiles from 1,893 respondents, in up to 30 tasks of 1 profile varying on 7 attributes.
| Description | 1,893 US Lucid respondents (January 2021) rated up to 30 single profiles of a hypothetical person (race, gender, marital status, number of children, immigration status, employment status, criminal record) on how typical the person is of welfare recipients, 0-10, under one of two instruction versions. The article analyses the 1,293 non-Hispanic white respondents. |
|---|---|
| Reference | Myers, C. D., Zhirkov, K., & Lunz Trujillo, K. (2024). Who is "on welfare"? Validating the use of conjoint experiments to measure stereotype content. Political Behavior, 46, 89-110. |
| DOI | 10.1007/s11109-022-09815-0 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/6ECD1D |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,893 |
|---|---|
| Rows (one per respondent, task and profile) | 56,655 |
| Tasks per respondent (most) | 30 |
| Profiles per task | 1 |
| Attributes | 7 |
| Topic | tax welfare economy |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| rating | How typical is the person described in the profile of welfare recipients? (paraphrase) [rating, 0 (unknown) to 10 (unknown)] |
|---|
attr_childrenattr_criminal_recordattr_employmentattr_genderattr_immigrationattr_maritalattr_racecov_agecov_educationcov_gendercov_hispaniccov_incomecov_party_id7cov_raceidprofileratingtasktrial_instruction_code
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("myers_2024_welfare_stereotypes", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("myers_2024_welfare_stereotypes", source="conj")
@article{Myers_2022, title={Who Is “On Welfare”? Validating the Use of Conjoint Experiments to Measure Stereotype Content}, volume={46}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-022-09815-0}, DOI={10.1007/s11109-022-09815-0}, number={1}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Myers, C. Daniel and Zhirkov, Kirill and Lunz Trujillo, Kristin}, year={2022}, month=Aug, pages={89–110} }
| 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 |