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Record W3021552611 · doi:10.3390/socsci9050068

One Step Forward, Two Steps Back: The Struggle for Child Protection in Canadian Sport

2020· article· en· W3021552611 on OpenAlexaffabout
Gretchen Kerr, Bruce Kidd, Peter Donnelly

Bibliographic record

VenueSocial Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeglectAthletesResistance (ecology)Public relationsControl (management)Suicide preventionPoison controlPsychologyPolitical scienceEnvironmental healthMedicinePsychiatryEconomicsManagementPhysical therapy

Abstract

fetched live from OpenAlex

Millions of children and adolescents around the world participate in organized sport for holistic health and developmental benefits. However, for some, sport participation is characterized by experiences of maltreatment, including forms of abuse and neglect. In Canada, efforts to address and prevent maltreatment in sport have been characterized by recurring cycles of crisis, public attention, policy response, sluggish implementation, and active resistance, with very little observable change. These cycles continue to this day. Achieving progress in child protection in Canadian sport has been hindered by the self-regulating nature of sport, funding models that prioritize performance outcomes, structures that deter athletes from reporting experiences of maltreatment, and inadequate attention to athletes’ recommendations and preventative initiatives. The culture of control that characterizes organized sport underpins these challenges to advancing child protection in sport. We propose that the establishment of a national independent body to provide safeguards against maltreatment in Canadian sport and to address this culture of control.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.512
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.041
GPT teacher head0.316
Teacher spread0.274 · 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.

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

Citations48
Published2020
Admission routes2
Has abstractyes

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