24,752 rated or chosen profiles from 1,768 respondents, in up to 7 tasks of 2 profiles varying on 6 attributes.
One of 5 tables from the same source; this one is the job_training_korea table. The others are listed under Related tables.
| Description | South Korean survey respondents (IFES 2023; n = 1,768) chose between two hypothetical people in 7 tasks of a job-training conjoint, profiles varying in age, family, gender, occupation, criminal record and origin (North Hamgyong, DPRK / Busan, ROK / Gyeonggi, ROK / Hanoi, Vietnam). Outcome: forced choice. |
|---|---|
| Reference | Brehm, N., Zhou, A. H., & Denney, S. (2025). From division to democracy: Integrating post-socialist citizens in Germany and South Korea. Communist and Post-Communist Studies. |
| DOI | 10.1525/cpcs.2025.2636997 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/WYBIAK |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,768 |
|---|---|
| Rows (one per respondent, task and profile) | 24,752 |
| Tasks per respondent (most) | 7 |
| Profiles per task | 2 |
| Attributes | 6 |
| Tasks with no profile chosen | 0 |
| Topic | tax welfare economy |
|---|---|
| A profile represents | person |
| Country | KR |
| Language shown | ko |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Which of the two people do you choose? (paraphrase) [choice, forced] |
|---|
attr_ageattr_familyattr_genderattr_occupationattr_originattr_recordchoicecov_ancestry_importancecov_birth_yearcov_birthplace_importancecov_educationcov_femalecov_korean_pridecov_national_compositioncov_national_identitycov_party_votecov_political_ideologycov_provincecov_support_nk_defectorscov_support_nk_engagementidprofiletask
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("brehm_2025_job_training_korea", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("brehm_2025_job_training_korea", source="conj")
@article{Brehm_2025, title={From Division to Democracy}, ISSN={1873-6920}, url={http://dx.doi.org/10.1525/cpcs.2025.2636997}, DOI={10.1525/cpcs.2025.2636997}, journal={Communist and Post-Communist Studies}, publisher={University of California Press}, author={Brehm, Robin and Zhou, Tianzi and Denney, Steven}, year={2025}, pages={1–24} }
| 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 |