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Record W2042918486 · doi:10.1080/17461390802086281

Defining and categorizing emotional abuse in sport

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.028
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