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Record W2340467396 · doi:10.1177/0193723515615176

Coaching, Touching, and False Allegations of Sexual Abuse in Canada

2015· article· en· W2340467396 on OpenAlexaffabout
Joannie Pépin-Gagné, Sylvie Parent

Bibliographic record

VenueJournal of Sport and Social Issues · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCoachingPerspective (graphical)False accusationPsychologySexual abuseSocial psychologySuicide preventionPoison controlMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Whether in sports training or in physical education contexts, touching is an integral component of the coaches’ tasks. However, recent evidence suggests that touching has become a significant concern for coaches in Canada and elsewhere, maybe due to the increased sensitivity toward child protection discourses. In fact, it appears that some coaches are concerned that touching children while coaching can potentially lead to false allegations of abuse by young people in their care or by the young person’s parents. These apprehensions are pushing some coaches to protect themselves by adopting various strategies or by avoiding certain situations, like touching. Recent evidence suggests that fears of false allegations can represent an obstacle for the prevention of sexual abuse. Moreover, these fears can have a significant impact on the victims of these crimes. Throughout this article, we explore the question of touching in coaching and the fears of false allegations of sexual abuse sometimes associated. The authors focus on understanding the foundations of these fears and offer some answers to the difficult questions that arise from this situation from a Canadian perspective.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0300.012
Scholarly communication0.0060.002
Open science0.0020.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.337
Teacher spread0.294 · 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 designObservational
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

Citations17
Published2015
Admission routes2
Has abstractyes

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