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Record W3203533455 · doi:10.1080/21640629.2021.1975940

A large and troubling iceberg: sexism and misogyny in women’s work as sport coaches

2021· article· en· W3203533455 on OpenAlexafffundabout
Sarah Barnes, Mary Louise Adams

Bibliographic record

VenueSports Coaching Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsQueen's UniversityCape Breton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHarassmentCoachingAthletesBasketballWork (physics)Public relationsCriminologyPsychologyPolitical scienceApplied psychologySocial psychologyEngineeringHistoryMedicine

Abstract

fetched live from OpenAlex

In the wake of a number of high profile cases, sport organisations in Canada, are taking abuse and harassment in sport more seriously. For the most part, recent initiatives have addressed the harms faced by athletes. This paper considers the harassment experienced by Canadian women coaches. The study is based on data from two focus groups (n = 4 and n = 5) held with women basketball and volleyball coaches. The coaches described a range of common experiences that would be classified as harassment under the Ontario Human Rights Code. Focusing here on the harassment perpetuated by male referees, we argue that such incidents stem from systemic issues in sport and in the broader culture. Our evidence suggests that misogyny and sexism need to be explicitly addressed in safe sport policies and in programmes designed to address the diminishing numbers of women in coaching.

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)0.010
metaresearch head score (Gemma)0.010
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 score0.171
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0060.012
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.312
Teacher spread0.284 · 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

Citations20
Published2021
Admission routes3
Has abstractyes

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