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Record W4306632846 · doi:10.4324/9781003035138

Gender-Based Violence in Children’s Sport

2022· book· en· W4306632846 on OpenAlexaff
Gretchen Kerr

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyGender studiesSociology

Abstract

fetched live from OpenAlex

"This book addresses the major forms of Gender-Based Violence (GBV) in children’s sport, including sexual, physical, and psychological violence and neglect. It reviews the historical, sociocultural, and political influences on violence towards children, and sets out future agendas for research and practice to eliminate GBV in sport. The book argues that for GBV to occur and be sustained over time, it must be facilitated by a system that enables this violence, protects the perpetrator, disables bystanders, silences the victims, and/or fails to provide a structure by which to address victims’ or bystanders’ concerns. Drawing on empirical research from across a range of disciplines, including sport sociology, sport psychology, developmental psychology, and coaching, and examining real life case studies of GBV in sport at all levels, the book makes a powerful case for radical change in our current systems of sport governance, safeguarding, and athlete welfare. This is important reading for any student, researcher, policy-maker, coach, welfare officer or counsellor with an interest in sport, gender studies, safeguarding, criminology, or sociology."

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.425
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

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