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Record W3038408203 · doi:10.1177/0146167220921065

Implicit Transgender Attitudes Independently Predict Beliefs About Gender and Transgender People

2020· article· en· W3038408203 on OpenAlexaff
Jordan Axt, Morgan Conway, Erin Corwin Westgate, Nicholas R. Buttrick

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransgenderPsychologySocial psychologyTransgender peopleTransgender PersonGender identityPsychoanalysis

Abstract

fetched live from OpenAlex

Surprisingly little is known about transgender attitudes, partly due to a need for improved measures of beliefs about transgender people. Four studies introduce a novel Implicit Association Test (IAT) assessing implicit attitudes toward transgender people. Study 1 ( N = 294) found significant implicit and explicit preferences for cisgender over transgender people, both of which correlated with transphobia and transgender-related policy support. Study 2 ( N = 1,094) found that implicit transgender attitudes predicted similar outcomes among participants reporting no explicit preference for cisgender versus transgender people. Across Study 3a ( N = 5,647) and Study 3b ( N = 2,276), implicit transgender attitudes predicted multiple outcomes, including gender essentialism, contact with transgender people, and support for transgender-related policies, over and above explicit attitudes. This work introduces a reliable means of measuring implicit transgender attitudes and illustrates how these attitudes independently predict meaningful beliefs and experiences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.364
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations59
Published2020
Admission routes1
Has abstractyes

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