Replication Data for: Measuring Gender in Comparative Survey Research (doi:10.7910/DVN/V0P7CN)

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Replication Data for: Measuring Gender in Comparative Survey Research

doi:10.7910/DVN/V0P7CN

Harvard Dataverse

2025-03-26

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Castorena, Oscar; Rau, Eli G.; Schweizer-Robinson, Valerie; Zechmeister, Elizabeth J., 2025, "Replication Data for: Measuring Gender in Comparative Survey Research", https://doi.org/10.7910/DVN/V0P7CN, Harvard Dataverse, V1, UNF:6:t/zCXaBXRmXXZEE7rb2YdA== [fileUNF]

Replication Data for: Measuring Gender in Comparative Survey Research

doi:10.7910/DVN/V0P7CN

Castorena, Oscar

Rau, Eli G.

Schweizer-Robinson, Valerie

Zechmeister, Elizabeth J.

Harvard Dataverse

Rau, Eli

Rau, Eli

2025-03-10

https://doi.org/10.7910/DVN/V0P7CN

Social Sciences

As societal conceptions of gender have evolved, so too have survey-based approaches to the measurement of gender. Yet, most research innovations and insights regarding the measurement of gender come from online or phone surveys in the Global North. We focus on face-to-face surveys in the Global South – in particular, the Latin America and Caribbean (LAC) region. Through in-person interviews, an online experiment, and survey experiments, we identify and assess an open-ended approach to incorporating respondent-provided gender identity in face-to-face interviews. Our results affirm the measure is comparatively effective in minimizing discomfort and does not have substantial consequences for data quality across a diverse set of LAC countries. We discuss the potential traveling capacity of our approach and we identify paths for further research on best practices in recording interviewee gender in face-to-face surveys in the LAC region and beyond.

• Number of cases: 1574

• No. of variables per record: 25

• Type of File: text/tab-separated-values

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• Number of cases: 1535

• No. of variables per record: 25

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• Number of cases: 1657

• No. of variables per record: 25

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• Number of cases: 3811

• No. of variables per record: 11

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• Number of cases: 43074

• No. of variables per record: 5

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• Number of cases: 2828

• No. of variables per record: 39

• Type of File: text/tab-separated-values

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• Number of cases: 1626

• No. of variables per record: 12

• Type of File: text/tab-separated-values

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README.txt

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1-import-and-clean.R

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AB2023-gender-analysis.do

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fig-1-a1-a2-attrition-nr.R

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