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Record W4389205633 · doi:10.1080/17430437.2023.2286017

Similarities and differences in male and female First Nations hockey players’ experiences of moving away from their home communities to play elite hockey in the Canadian mainstream context

2023· article· en· W4389205633 on OpenAlexaffabout
Jaime Carpenter, Audrey R. Giles

Bibliographic record

VenueSport in Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEliteMainstreamGender studiesContext (archaeology)Ice hockeyRacismIndigenousField hockeyAthletesSociologyPsychologyPolitical sciencePoliticsMedia studiesMedicineGeographyLawPhysical therapy

Abstract

fetched live from OpenAlex

There is a dearth of research that has explored the differences and similarities in First Nations male and female hockey players’ experiences while playing elite hockey in the Canadian mainstream. I used tribal critical race theory, Indigenous feminisms, Indigenous methodologies, and interviews with 10 male and 10 female First Nations elite hockey players to understand the differences and similarities in their experiences of moving away from home to pursue hockey in the mainstream. I produced two main themes: the challenges that the athletes experienced, which included new languages, culture shock, and racism; and the benefits, which were athletic and personal growth and support from their home community. There were important differences between male and female participants, which included the males facing more violent and overt racism than the female players, and the female players needing to travel farther away from home due to a lack of opportunities to play hockey.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.040
GPT teacher head0.264
Teacher spread0.225 · 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 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
Published2023
Admission routes2
Has abstractyes

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