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

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

About this table

Description	2,401 Mexican online respondents read about more municipal police officers hired, with the officers' sex (female, or not named) and previous background (soldiers, private security, self-defence forces, human rights activists, migrants in the US, or none) randomized; outcomes: 1-4 faith that they catch criminals and 1-4 likelihood of abuses.
Reference	López García, A. I., Berens, S., & Maydom, B. (2023). MigCrimeMexSurvey 2021 [Data set]. Harvard Dataverse.
Licence	CC0 1.0
Source data	https://doi.org/10.7910/dvn/byavmc

Notes

Conjoint table (irw_conjoint_2). Factorial vignette, one per respondent: 'authorities hire more [female] municipal police officers [who previously worked as soldiers / in private security / were self-defence force members / human rights activists / migrants in the US]', control clauses '(not shown)'. rating_faith: faith they would catch the criminals if you were a victim (1 = not at all, 4 = a lot); rating_abuse_likelihood: how likely they would commit bribery, torture, discrimination, abuse or false arrest (1 = not likely, 4 = very likely). Balanced 2x6 design. Level text translated from the questionnaire.

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

Design

Topic	crime justice policing
A profile represents	person
Country	MX
Language shown	es
Language of stored levels	en
Randomization restrictions	unknown
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_abuse_likelihood	If the government recruited more municipal police officers <female> <background>, how likely do you think it would be that these agents would incur in activities (such as bribery, torture, discrimination, aggression, verbal abuse, sexual abuse or false arrest) when arresting criminals or investigating the case? [rating, 1 (Not likely) to 4 (Very likely)]
rating_faith	If authorities hire more <female> municipal police officers <background>, how much faith would you have that these policemen catch the criminals, if you were a victim of a robbery or assault? [rating, 1 (Not at all) to 4 (A lot)]

Columns

attr_officer_backgroundattr_officer_sexcov_agecov_age_groupcov_educationcov_gendercov_stateidprofilerating_abuse_likelihoodrating_faithtask

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("lopezgarcia_2023_mx_police_recruits", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("lopezgarcia_2023_mx_police_recruits", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/byavmc,
  doi = {10.7910/DVN/BYAVMC},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/BYAVMC},
  author = {Lopez Garcia, Ana Isabel and Berens, Sarah and Maydom, Barry},
  keywords = {Social Sciences},
  title = {Replication Data for: Emigration, Social Remittances and Fiscal Policy Preferences: Experimental Evidence from Mexico.},
  publisher = {Harvard Dataverse},
  year = {2023}
}

Respondents	2,401
Rows (one per respondent, task and profile)	2,401
Tasks per respondent (most)	1
Profiles per task	1
Attributes	2

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

lopezgarcia_2023_mx_police_recruits