10,972 rated or chosen profiles from 1,099 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.
One of 2 tables from the same source; this one is the conjoint table. The others are listed under Related tables.
| Description | US YouGov respondents (n=1,099; general-population sample plus Black oversample, spring 2022) chose in 5 tasks which of two police officer profiles would make them most afraid; officers varied race, gender, age, build, education, body camera and prior complaints. |
|---|---|
| Reference | Pickett, J. T., Graham, A., Nix, J., & Cullen, F. T. (2024). Officer diversity may reduce Black Americans' fear of the police. Criminology, 62(1), 35-63. |
| DOI | 10.1111/1745-9125.12360 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/ASL3JD |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,099 |
|---|---|
| Rows (one per respondent, task and profile) | 10,972 |
| Tasks per respondent (most) | 5 |
| Profiles per task | 2 |
| Attributes | 7 |
| Tasks with no profile chosen | 0 |
| Topic | crime justice policing |
|---|---|
| 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:
| choice | Which officer in this pairing would make you the most afraid? (paraphrase) [choice, forced] |
|---|
attr_ageattr_buildattr_cameraattr_complaintattr_educationattr_genderattr_raceattrpos_ageattrpos_buildattrpos_cameraattrpos_complaintattrpos_educationattrpos_genderattrpos_racechoicecov_birth_yearcov_educationcov_fear_police_1cov_fear_police_10cov_fear_police_2cov_fear_police_3cov_fear_police_4cov_fear_police_5cov_fear_police_6cov_fear_police_7cov_fear_police_8cov_fear_police_9cov_gendercov_party_id7cov_racecov_samplecov_survey_weightidprofiletask
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("pickett_2024_officer_conjoint", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("pickett_2024_officer_conjoint", source="conj")
@article{Pickett_2023, title={Officer diversity may reduce Black Americans’ fear of the police}, volume={62}, ISSN={1745-9125}, url={http://dx.doi.org/10.1111/1745-9125.12360}, DOI={10.1111/1745-9125.12360}, number={1}, journal={Criminology}, publisher={Wiley}, author={Pickett, Justin T. and Graham, Amanda and Nix, Justin and Cullen, Francis T.}, year={2023}, month=Dec, pages={35–63} }
| IRW version | v607 |
|---|---|
| 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 v47.0 |