36,500 rated or chosen profiles from 9,125 respondents, in up to 4 tasks of 1 profile varying on 5 attributes.
| Description | Adults in nine European countries (Bilendi panels, Feb-Mar 2023; n=9,125) each saw 4 single hypothetical person profiles varying EU attitude, immigration attitude, class, education and age, and judged whether the person typically lives in a rural or urban area, how sure they were, and rated the person on a 0-100 feeling thermometer. |
|---|---|
| Reference | Hegewald, S. (2026). The urban-rural divide in people's minds: Stereotypes of urbanites and ruralites in nine European countries. Political Behavior. |
| DOI | 10.1007/s11109-026-10160-9 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/8F5FQB |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 9,125 |
|---|---|
| Rows (one per respondent, task and profile) | 36,500 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 1 |
| Attributes | 5 |
| Topic | social identity interpersonal |
|---|---|
| A profile represents | person |
| Country | CZ, DE, DK, GR, ES, FR, HU, IT, PL |
| Language shown | cs, de, da, el, es, fr, hu, it, pl |
| Language of stored levels | en |
| Task order | recorded in the deposit |
| 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 | Looking again at the description of the person above, we now want you to rate this person on a so-called 'feeling thermometer'. Scores between 50 and 100 mean that you have positive and warm feelings toward this person. Scores between 0 and 50 mean you feel cold and negative about this person. A score of 50 means you feel neither warm nor cold about this person. Looking at this person, how do you feel? [rating, 0 (cold and negative) to 100 (positive and warm)] |
|---|---|
| rating_rural | Looking at the description of the person above, do you think that this person typically lives in an urban area or typically lives in a rural area? [rating, 0 (typically lives in an urban area) to 1 (typically lives in a rural area)] |
| rating_sureness | You have indicated that the person shown above *typically lives in an urban area/typically lives in a rural area*. How sure are you about this choice? [rating, 1 (very sure) to 4 (very unsure)] |
attr_ageattr_classattr_educationattr_euattr_immigrationcov_agecov_countrycov_educationcov_eu_membershipcov_immigrationcov_income_decilecov_residenceidprofileratingrating_ruralrating_surenesstask
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("hegewald_2026_urban_rural", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("hegewald_2026_urban_rural", source="conj")
@article{Hegewald_2026, title={The Urban–Rural Divide in People’s Minds: Stereotypes of Urbanites and Ruralites in Nine European Countries}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-026-10160-9}, DOI={10.1007/s11109-026-10160-9}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Hegewald, Sven}, year={2026}, month=May }
| 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 |