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Record W4409083822 · doi:10.1017/s1049096525000010

Transgender Bodies are the Battleground: Backlash, Threat, and the Future of Queer Rights in the United States

2025· article· en· W4409083822 on OpenAlexaff
Kaitlin Kelly-Thompson, Amber Lusvardi

Bibliographic record

VenuePS Political Science & Politics · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBacklashQueerTransgenderPolitical scienceGay rightsGender studiesLawCriminologySociologyEngineeringPolitics

Abstract

fetched live from OpenAlex

Abstract Legislation that seeks to restrict the ability of transgender people to fully participate in society has proliferated across state legislatures in the last four years. In legislative sessions throughout the United States, legislators have argued in favor of denying transgender people access to public facilities, sports, health care, and even their own guardians. What can these debates tell us not only about the backlash against transgender people but the queer community and women more broadly? Using an analysis of the debate on anti-transgender legislation in two state legislatures, we argue that legislators attempt to gain support for anti-transgender legislation using paternal, protectionist frames and by coopting the language of feminism. We argue that the gender essentialism and heteronormativity at the center of these debates indicates an attempt on behalf of conservative movements and legislators to pursue an idealized, heteropatriarchal society with a strict gender binary.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.024
Scholarly communication0.0120.006
Open science0.0010.005
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.028
GPT teacher head0.372
Teacher spread0.344 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2025
Admission routes1
Has abstractyes

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