christensen_2020_participatory

10,500 rated or chosen profiles from 1,050 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.

About this table

DescriptionPaired conjoint on participatory processes: 1,050 Finnish adults (Qualtrics panel) chose between two hypothetical participatory processes in 5 comparisons, varying policy issue, inclusiveness, number of gatherings, transparency, online vs face-to-face meetings, how participants form judgements and whether the outcome is binding or advisory; outcome is a forced choice.
ReferenceChristensen, H. S. (2020). How citizens evaluate participatory processes: A conjoint analysis. European Political Science Review, 12(2), 239-253.
DOI10.1017/S1755773920000107
LicenceCC BY 4.0
Source datahttps://osf.io/cjn6u/

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

Respondents1,050
Rows (one per respondent, task and profile)10,500
Tasks per respondent (most)5
Profiles per task2
Attributes7
Tasks with no profile chosen0

Design

Topicdemocracy institutions
A profile representspolicy
CountryFI
Language shownunknown
Language of stored levelsen
Task orderinferred from row order
Profile positioninferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choiceWhich of the two participatory processes do you prefer? (paraphrase) [choice, forced]

Columns

attr_considered_judgementattr_efficiencyattr_inclusivenessattr_policy_issueattr_popular_controlattr_transferabilityattr_transparencychoiceidprofiletask

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("christensen_2020_participatory", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("christensen_2020_participatory", source="conj")

How to cite

@article{Christensen_2020, title={How citizens evaluate participatory processes: a conjoint analysis}, volume={12}, ISSN={1755-7747}, url={http://dx.doi.org/10.1017/S1755773920000107}, DOI={10.1017/s1755773920000107}, number={2}, journal={European Political Science Review}, publisher={Cambridge University Press (CUP)}, author={Christensen, Henrik Serup}, year={2020}, month=Mar, pages={239–253} }

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