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Record W2014769879 · doi:10.1504/ijsmm.2007.013709

A multidimensional critique of the Sport Canada Policy on Women in Sport and its implementation in one national sport organisation

2007· article· en· W2014769879 on OpenAlexaffabout
Jennifer L. Myers, Alison Doherty

Bibliographic record

VenueInternational Journal of Sport Management and Marketing · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern UniversitySt. Thomas University
Fundersnot available
KeywordsGender equityEquity (law)Sport managementPublic relationsSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

A multidimensional framework that purports the need to address individual, structural and cultural barriers to gender equity in sport was used as a basis for the deductive analysis of the existing Sport Canada Policy on Women in Sport and related strategies and initiatives of one National Sport Organisation (NSO) between 1986 and 2004. Structural initiatives appeared to be the main emphasis of the Women in Sport Policy, while the NSO's initiatives in response to that policy predominantly focussed on individual barriers. The analysis further revealed five key events that represented a shift in the NSO's overall gender equity strategy over the 18-year period, from an individual to a more structural perspective. One NSO initiative in particular the women's national team represented a multidimensional approach, addressing individual, structural and cultural barriers to gender equity and producing positive results for the NSO.

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)0.031
metaresearch head score (Gemma)0.038
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0250.057
Scholarly communication0.0140.004
Open science0.0040.006
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.323
Teacher spread0.309 · 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

Citations5
Published2007
Admission routes2
Has abstractyes

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