floresmacias_2022_militarization

2,410 rated or chosen profiles from 1,205 respondents, in up to 1 tasks of 2 profiles varying on 4 attributes.

About this table

Description1,205 Mexican respondents each saw one pair of photographs of security personnel varying in uniform (police/military), weapon, gender and skin colour; outcomes are a forced choice of who is more effective and four 0-1 ratings (effectiveness, civil liberties, corruption, acceptance in own neighbourhood).
ReferenceFlores-Macías, G., & Zarkin, J. (2022). Militarization and perceptions of law enforcement in the developing world: Evidence from a conjoint experiment in Mexico. British Journal of Political Science, 52(3), 1377-1397.
DOI10.1017/S0007123421000259
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/UMUEOK

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

Respondents1,205
Rows (one per respondent, task and profile)2,410
Tasks per respondent (most)1
Profiles per task2
Attributes4
Tasks with no profile chosen0

Design

Topiccrime justice policing
A profile representsperson
CountryMX
Language shownunknown
Language of stored levelsen
Randomization restrictionsobserved in the data (not documented by the source): the two photos in a pair always differ (0 identical pairs of 1,205; ~75 expected under independent draws of the 16 photos)
Task orderinferred from row order
Profile positionrecorded in the deposit

Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead. Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choiceForced choice, who is more effective (paraphrase) [choice, forced]
rating_civil_libertiesRating civil liberties (paraphrase) [rating, 0 (unknown) to 1 (unknown)]
rating_corruptRating corrupt (paraphrase) [rating, 0 (unknown) to 1 (unknown)]
rating_effectiveRating effectivenes (paraphrase) [rating, 0 (unknown) to 1 (unknown)]
rating_neighborhoodRating neighborhood (paraphrase) [rating, 0 (unknown) to 1 (unknown)]

Columns

attr_genderattr_skin_colorattr_uniformattr_weaponchoicecov_agecov_educationcov_gendercov_ideologycov_party_idcov_skin_tonecov_statecov_trust_armycov_victimidprofilerating_civil_libertiesrating_corruptrating_effectiverating_neighborhoodtasktrial_prompt

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("floresmacias_2022_militarization", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("floresmacias_2022_militarization", source="conj")

How to cite

@article{Flores_Mac_as_2021, title={Militarization and Perceptions of Law Enforcement in the Developing World: Evidence from a Conjoint Experiment in Mexico}, volume={52}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123421000259}, DOI={10.1017/s0007123421000259}, number={3}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Flores-Macías, Gustavo and Zarkin, Jessica}, year={2021}, month=July, pages={1377–1397} }

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