kamalov_2026_emigrant_aid

8,144 rated or chosen profiles from 2,036 respondents, in up to 2 tasks of 2 profiles varying on 6 attributes.

About this table

DescriptionRussian migrants who left Russia in 2022 (convenience sample in 60+ countries, n=2,036) chose, in 2 tasks, which of two hypothetical Russian individuals (varying age, gender, children, profession, ethnic origin and motivation for emigrating) they preferred to help.
ReferenceKamalov, E., & Sergeeva, I. (2026). Helping emigrants flee a political crisis: How antiwar alignment shapes the aid preferences of wartime Russian migrants. Perspectives on Politics.
DOI10.1017/S1537592725104143
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/NFQHIM

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents2,036
Rows (one per respondent, task and profile)8,144
Tasks per respondent (most)2
Profiles per task2
Attributes6
Tasks with no profile chosen0

Design

Topicimmigration asylum, social identity interpersonal
A profile representsperson
Countryunknown
Language shownru
Language of stored levelsen
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceChoose which of two profiles of hypothetical Russian individuals you prefer to help (paraphrase) [choice, forced]

Columns

attr_ageattr_childrenattr_ethnicityattr_genderattr_motivationattr_professionchoicecov_agecov_countrycov_educationcov_gendercov_guiltcov_has_childrencov_help_russian_emigrantscov_help_russian_ngoscov_help_ukrainian_refugeescov_incomecov_left_after_mobilizationcov_politics_interestcov_protest_permittedcov_protest_unpermittedcov_repression_countcov_responsibilityidprofiletask

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.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

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("kamalov_2026_emigrant_aid", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("kamalov_2026_emigrant_aid", source="conj")

How to cite

@article{Kamalov_2026, title={Helping Emigrants Flee a Political Crisis: How Antiwar Alignment Shapes the Aid Preferences of Wartime Russian Migrants}, ISSN={1541-0986}, url={http://dx.doi.org/10.1017/S1537592725104143}, DOI={10.1017/s1537592725104143}, journal={Perspectives on Politics}, publisher={Cambridge University Press (CUP)}, author={Kamalov, Emil and Sergeeva, Ivetta}, year={2026}, month=Mar, pages={1–15} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0