berens_2024_crime_measures

2,401 rated or chosen profiles from 2,401 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.

One of 4 tables from the same source; this one is the crime_measures table. The others are listed under Related tables.

About this table

DescriptionMexican adults (Pollfish online survey, 2021-22; n = 2,401) rated agreement that reducing crime needs more security forces on the streets, with the territorial scope and an accompanying social or punitive measure randomized (experiment 5, the article's experiment).
ReferenceBerens, S., López García, A. I., & Maydom, B. (2024). Classrooms or crackdowns? How violence affects security policy preferences in Mexico. Studies in Comparative International Development, 61(1), 10-33.
DOI10.1007/s12116-024-09445-z
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/W1YF9Y

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

Respondents2,401
Rows (one per respondent, task and profile)2,401
Tasks per respondent (most)1
Profiles per task1
Attributes2

Design

Topiccrime justice policing
A profile representspolicy
CountryMX
Language shownes
Language of stored levelses
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

ratingPor favor indique ¿qué tan de acuerdo está usted con la siguiente frase? “Para reducir y controlar el crimen <variación 1>, se necesitan a más fuerzas de seguridad en las calles <variación 2>” [rating, 1 (Muy en desacuerdo) to 5 (Muy de acuerdo)]

Columns

attr_measureattr_territorycov_agecov_age_groupcov_birth_yearcov_education_codecov_genderidprofileratingtask

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("berens_2024_crime_measures", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("berens_2024_crime_measures", source="conj")

How to cite

@article{Berens_2024, title={Classrooms or Crackdowns? How Violence Affects Security Policy Preferences in Mexico}, volume={61}, ISSN={1936-6167}, url={http://dx.doi.org/10.1007/s12116-024-09445-z}, DOI={10.1007/s12116-024-09445-z}, number={1}, journal={Studies in Comparative International Development}, publisher={Springer Science and Business Media LLC}, author={Berens, Sarah and López García, Ana Isabel and Maydom, Barry}, year={2024}, month=Oct, pages={10–33} }

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