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Record W2042918486 · doi:10.1080/17461390802086281

Defining and categorizing emotional abuse in sport

2008· article· en· W2042918486 on OpenAlexaff
Ashley Stirling, Gretchen Kerr

Bibliographic record

VenueEuropean Journal of Sport Science · 2008
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyApplied psychologyPsychological abuseClinical psychologyPoison controlInjury preventionMedicineChild abuseMedical emergency

Abstract

fetched live from OpenAlex

Abstract In this study, we used a qualitative research design to explore athletes’ experiences of emotional abuse in sport. Semi‐structured interviews were conducted with 14 retired, elite female swimmers, and data were analysed inductively using open, axial, and selective coding procedures. Findings revealed that emotionally abusive behaviours of the coach occurred in three ways: through physical behaviours, verbal behaviours, and the denial of attention and support. Based on our findings, a definition of emotional abuse in sport is proposed. This definition of emotional abuse is the first definition derived from the experiences of emotional abuse within an athletic environment. It encapsulates previous definitions of emotional abuse, types of emotionally abusive behaviours, and outcomes of these behaviours. The need for an athlete protection initiative in sport is discussed and recommendations are made for future research.

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)0.009
metaresearch head score (Gemma)0.018
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0040.011
Scholarly communication0.0050.004
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.293
Teacher spread0.265 · 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

Citations169
Published2008
Admission routes1
Has abstractyes

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