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Record W2888982860 · doi:10.1123/tsp.2018-0005

Elite Canadian Women Rugby Athletes’ Attitude to and Experience of Physical Aggression

2018· article· en· W2888982860 on OpenAlexaffabout
John Kerr

Bibliographic record

VenueThe Sport Psychologist · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAggressionPsychologyAthletesAngerThematic analysisSocial psychologyEliteInterpretation (philosophy)Qualitative researchPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

Elite Canadian women rugby union athletes’ (N = 10) attitude to and experience of physical aggression was investigated in this study. The methodology adopted in this postpositivist study was a deductive qualitative approach and involved theoretical thematic data analysis. The analysis and interpretation of data was informed by Kerr’s distinction between sanctioned and unsanctioned forms of aggression. Open-ended, semistructured interviews provided ample evidence that rugby provided pleasurable experiences through active physicality and sanctioned play aggression. With regard to unsanctioned aggression, backs and forwards recounted incidents of unsanctioned aggression perpetrated against them by opponents. Backs’ interview statements indicated no real involvement in unsanctioned aggression, but the majority of forwards had perpetrated acts of anger and power-unsanctioned aggression against opponents. No incidents of thrill-based unsanctioned aggression were described by the elite women athletes. Suggestions for future aggression research are discussed.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.030
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.363
Teacher spread0.329 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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