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Record W2794335258 · doi:10.1177/0193723518758456

“There’s a Cultural Pride Through Our Games”: Enhancing the Sport Experiences of Indigenous Youth in Canada Through Participation in Traditional Games

2018· article· en· W2794335258 on OpenAlexafffundabout
Michael Dubnewick, Tristan Hopper, John C. Spence, Tara-Leigh McHugh

Bibliographic record

VenueJournal of Sport and Social Issues · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaParker Foundation
KeywordsPrideIndigenousParticipatory action researchCitizen journalismSociologyPublic relationsPsychologyPolitical science

Abstract

fetched live from OpenAlex

The purpose of this community-based participatory research was to better understand how participation in traditional games can enhance the sport experiences of Indigenous youth. Eight Indigenous youth (14-18 years) and 10 adults living in various communities in the Northwest Territories, Canada, participated in either a one-on-one interview or group interview. Data were analyzed using an inductive content analysis approach, and findings suggest that participating in traditional games can enhance the sport experiences of Indigenous youth by (a) promoting cultural pride, (b) interacting with Elders, (c) supporting connection to the land, (d) developing personal characteristics, and (e) developing a foundation for movement. This research advances the sport literature and provides necessary insights regarding traditional games for sport programmers and policy makers.

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)0.002
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 score0.137
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.055
GPT teacher head0.336
Teacher spread0.282 · 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

Citations45
Published2018
Admission routes3
Has abstractyes

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