Alternative Gender Measures Survey

Principal Investigator(s):  View help for Principal Investigator(s) Aliya Saperstein, Stanford University; Laurel Westbrook, Grand Valley State University

Version:  View help for Version V1

Name File Type Size Last Modified
  Do-files-for-replication 04/30/2019 05:59:PM
AGMS_Codebook.pdf application/pdf 1.7 MB 05/02/2019 09:20:AM
AlternativeGenderMeasuresSurvey.dta application/x-stata 1.9 MB 05/01/2019 05:14:PM

Project Citation: 

Saperstein, Aliya, and Westbrook, Laurel. Alternative Gender Measures Survey. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-05-02. https://doi.org/10.3886/E109542V1

Project Description

Summary:  View help for Summary The Alternative Gender Measures Survey (AGMS) was conducted on Amazon Mechanical Turk in November 2014 to pilot measures as part of a proposal for a new sex and gender module in the General Social Survey (GSS). In order to test the measures in a realistic context, a six-item sex and gender module was embedded in a questionnaire designed to approximate conventional questionnaires in the social sciences. Most of the items were drawn from the GSS and have the same question wording and variable names.

The AGMS sex and gender module includes: a pair of feminine and masculine scales asked from the first-order (how do you see yourself?) perspective, a pair of feminine and masculine scales asked from the third-order (how do most people see you?) perspective, and a two-step categorical measurement of sex at birth and current gender identity. This two-step approach is the same one adopted by the GSS for its 2018 survey.
Funding Sources:  View help for Funding Sources American Sociological Association Fund for the Advancement of the Discipline; Clayman Institute for Gender Research

Scope of Project

Subject Terms:  View help for Subject Terms gender; testing and measurement; social inequality; social attitudes
Geographic Coverage:  View help for Geographic Coverage United States
Collection Date(s):  View help for Collection Date(s) 11/4/2014 – 11/24/2014
Universe:  View help for Universe U.S. residents, age 18 and older
Data Type(s):  View help for Data Type(s) survey data
Collection Notes:  View help for Collection Notes Survey was fielded on Amazon Mechanical Turk. See codebook for details on randomized question ordering and other aspects of the survey design.


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V1 [2019-05-02]

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