1,210 rated or chosen profiles from 121 respondents, in up to 10 tasks of 1 profile varying on 3 attributes.
One of 2 tables from the same source; this one is the resume_pretest table. The others are listed under Related tables.
| Description | 121 respondents (pretest; sample not described) each rated 10 hypothetical job applicants, varying master's major, highlighted courses and extracurricular study group (socialist vs Western), on academic merit, government connections and political conformity (1-10 each). |
|---|---|
| Reference | Pan, J., & Zhang, T. (2023). Does ideology influence hiring in China? Evidence from two randomized experiments. Political Science Research and Methods, 11(1), 63-79. |
| DOI | 10.1017/psrm.2021.77 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/CLZZTW |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 121 |
|---|---|
| Rows (one per respondent, task and profile) | 1,210 |
| Tasks per respondent (most) | 10 |
| Profiles per task | 1 |
| Attributes | 3 |
| Topic | labour hiring |
|---|---|
| A profile represents | person |
| Country | unknown |
| Language shown | unknown |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | unknown |
| Profile position | recorded in the deposit |
Outcomes:
| rating_conformity | respondent's rating (on the scale of 1-10) of political conformity to the Chinese Communist Party (CCP) regime for each applicant (paraphrase) [rating, 1 (unknown) to 10 (unknown)] |
|---|---|
| rating_connections | respondent's rating (on the scale of 1-10) of the strength of government connections for each applicant (paraphrase) [rating, 1 (unknown) to 10 (unknown)] |
| rating_merit | respondent's rating (on the scale of 1-10) of academic merit for each applicant (paraphrase) [rating, 1 (unknown) to 10 (unknown)] |
attr_coursesattr_extracurricularattr_majoridprofilerating_conformityrating_connectionsrating_merittask
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("pan_2023_resume_pretest", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("pan_2023_resume_pretest", source="conj")
@article{Pan_2022, title={Does ideology influence hiring in China? evidence from two randomized experiments}, volume={11}, ISSN={2049-8489}, url={http://dx.doi.org/10.1017/psrm.2021.77}, DOI={10.1017/psrm.2021.77}, number={1}, journal={Political Science Research and Methods}, publisher={Cambridge University Press (CUP)}, author={Pan, Jennifer and Zhang, Tongtong}, year={2022}, month=Feb, pages={63–79} }
| 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 |