21,561 rated or chosen profiles from 21,561 respondents, in up to 1 tasks of 1 profile varying on 3 attributes.

One of 3 tables from the same source; this one is the park_cleanup table. The others are listed under Related tables.

About this table

Description	21,561 respondents in 14 post-communist countries (PGPE survey, 2013-2014) each saw one version of a vignette about a local park clean-up initiative (how often you and your family go to the park, how many people you know plan to join, and an incentive) and rated how likely they were to join an initiative to clean up a local park (1 very likely to 4 not likely at all).
Reference	Letki, N. (2025). Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe [Data set]. Dane Badawcze UW.
Licence	CC BY 4.0
Source data	https://doi.org/10.58132/sbjiw0

Notes

Conjoint table (irw_conjoint_2). Factorial vignette (3 x 3 x 3, full factorial), one per respondent: rating = 'How likely is it that YOU will join this initiative to clean up a local park?' on a 4-point card, 1 = very likely ... 4 = not likely at all (lower = more likely; 'Don't know' and 'Refusal' removed). Fourteen countries pooled (cov_country) on the English master text; the translated wording is not in the deposit. The incentive attribute is '(not shown)' when omitted. Survey weight kept; id = row of the source file. N = 21,561 respondents of 22,039.

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

Design

Topic	social identity interpersonal
A profile represents	scenario
Country	BG, HR, CZ, EE, HU, LV, LT, MD, PL, RO, RS, SK, SI, UA
Language shown	unknown
Language of stored levels	en
Task order	inferred from row order
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	How likely is it that YOU will join this initiative to clean up a local park? (master English questionnaire, card A03) [rating, 1 (Very likely) to 4 (Not likely at all)]

Columns

attr_incentiveattr_others_joiningattr_visit_frequencycov_age_groupcov_birth_yearcov_countrycov_educationcov_survey_weightidprofileratingtask

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 needed Browse on Redivisexplore and query Croissant 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("letki_2025_park_cleanup", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("letki_2025_park_cleanup", source="conj")

How to cite

@misc{https://doi.org/10.58132/sbjiw0,
  doi = {10.58132/SBJIW0},
  url = {https://danebadawcze.uw.edu.pl/citation?persistentId=doi:10.58132/SBJIW0},
  author = {Letki, Natalia},
  title = {Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe},
  publisher = {Dane Badawcze UW},
  year = {2025}
}

Version and provenance

IRW version	v584
Redivis dataset	irw_conjoint_2 v1.4
Redivis dataset DOI	10.57761/hk97-wv30
Manifest pin for this IRW version	v1.4
Metadata source	irw_meta v44.0

Respondents	21,561
Rows (one per respondent, task and profile)	21,561
Tasks per respondent (most)	1
Profiles per task	1
Attributes	3

letki_2025_park_cleanup