Gender Affinity and Identity in Candidate Support Conjoint Data

Alejandro Tirado Castro produced this conjoint experiment dataset in 2026 to analyze how gender identity affects political candidate support. It contains experimental responses measuring voter preferences for candidates alongside psychometric scales for hyper-masculinity and hyper-femininity.

Use Cases

• Evaluating the impact of hyper-femininity scores on candidate selection
• Testing gender affinity effects by comparing respondent gender with candidate gender attributes
• Replicating statistical models of voter behavior from the original Research & Politics publication

Strengths

• Includes measures for hyper-masculinity and hyper-femininity
• Uses a conjoint experiment design to isolate candidate attributes
• Peer-reviewed replication data from Research & Politics

Limitations

• Sample size and demographic distribution are not specified in the metadata
• Relies on self-reported gender identity measures which may be subject to social desirability bias

Provenance

Source

Research & Politics Dataverse

Collection Method

conjoint experiment

Freshness

Last updated March 2026.