Sport, Self-esteem, and Identity among Indigenous Individuals and Communities
Bibliographic record
Abstract
Background: Within Indigenous communities, sports hold prominent importance in cultures and traditions, serving not only as a means of imparting valuable skills but also contributing to mental, physical, and spiritual well-being. Sports enhance one’s sport-related competencies while also having links to an individual’s feelings of self-esteem and self-identity. Purpose: The purpose of this paper is to explore the connections between sports participation, self-esteem, and identity within North American Indigenous communities, with an emphasis on Indigenous communities in Canada. Methods: A narrative review of existing literature, along with an environmental scan, was employed. Results: Sports create robust community ties, nurturing a sense of belonging and elevating self-esteem among Indigenous individuals. The integration of traditional Indigenous sports and teachings amplifies authenticity in self-esteem, validating personal identities and cultural values. Accurate representation of Indigenous athletes in media enhances self-efficacy and elicits collective pride and resilience, strengthening Indigenous peoples and communities’ sense of identity. Conclusion: Three key findings highlight ways that participation in sports supports self-esteem and identity among Indigenous peoples and communities: connections to community and meaningful relationships, engagement in traditional Indigenous sports, and accurate representation of Indigenous athletes in the media.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".