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Conclusion: Resistance: The Way Forward

2023· book-chapter· en· W4387774979 on OpenAlexaffabout
Helen Jefferson Lenskyj, Ali Durham Greey

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMainstreamSolidarityTransformative learningResistance (ecology)Political scienceAthletesEmpowermentInclusion (mineral)Public relationsFeminismSociologyGender studiesLawPoliticsMedicinePedagogy

Abstract

fetched live from OpenAlex

Abstract This chapter investigates resistance initiated by trans athletes and their allies and evaluates developments in policies and practices at the international, national and local levels of sport. The limitations of liberal approaches to trans inclusion are identified, and examples of radical, transformative approaches grounded in intersectional feminism are presented, together with an analysis of the crucial roles of solidarity work provided by allies and accomplices. The potential offered by boxing as a route to empowerment for trans and nonbinary participants is examined. An overview of recent media coverage of trans athletes suggests that global resistance is having an important impact on mainstream journalism. Finally, this chapter outlines how a successful campaign challenging a trans-exclusive Sport Canada's 2022 opinion survey and a recent report by Canadian Centre for Ethics in Sport provide further evidence of effective resistance to trans exclusion in sport.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0130.013
Open science0.0030.006
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0350.012

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 head0.039
GPT teacher head0.308
Teacher spread0.269 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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