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Record W4413828479 · doi:10.5040/9781350449893

Polarising Sexualities and Genders

2025· book· en· W4413828479 on OpenAlexaboutno aff

Bibliographic record

VenueBloomsbury Publishing Plc eBooks · 2025
Typebook
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
Fundersnot available
KeywordsHuman sexualityGender studiesSociology

Abstract

fetched live from OpenAlex

<JATS1:p>This ground-breaking open access collection tackles polarisations around sexualities and genders and in doing so, it opens out debates and discussions to reflect on how people live them, including and moving beyond social movements and political debates.</JATS1:p> <JATS1:p>Anti-gender and heteroactivist movements have become increasingly recognized as key political groups in the last decade, driving resistances that often respond to LGBTQI+ inclusion. How these divisions are felt and experienced is under-explored.</JATS1:p> <JATS1:p>Crossing a variety of geographical contexts, including India, USA, Canada, Ireland, and Great Britain, Polarising Sexualities and Genders brings together leading and emerging scholars in multiple disciplines to explore, theorise and hope for change in social, legal, and political sexual/gendered/LGBTQIA+ landscapes. Examples include polarisation in media coverage and legislative debates about gender and transgender rights in the US and UK, to the possibility of occupying a sexual borderlands, the changing language for LGBTQIA+identities within the US, and the ways in which new discourses emerge to capture sexual lives. Through these case studies, the book explores how polarizing discourses and sociopolitical landscape shape the lived experiences, divisions, and marginalizations among LGBTQIA+ people in places including Lithuania, South India and the southern United States.</JATS1:p> <JATS1:p>The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by the European Research Council.</JATS1:p>

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.290
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2025
Admission routes1
Has abstractyes

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