Indigenous Identity Development through Sport
Bibliographic record
Abstract
Physical activity, games, sport and youth have a rich history within Indigenous communities, but that is not reflected in academic literature. For years, scholars wrote about Indigenous communities and people and not with them. Aspects of everyday life, such as physical activity, games and sport were seen as trivial and often marginalized. By listening to the narratives of Indigenous youth we get an understanding of the complexities of their lives. Research for, by and with Indigenous communities is growing. This thesis examines the idea of Indigenous identity navigation through sport by using an Indigenous research methodology, the strengths approach, the framework of two-eyed seeing and a community based participatory research strategy. The method for collecting data was through individual interviews and a traditional Indigenous talking circle. The research question and interview questions were developed with the community-based research assistant. Participants/Coresearchers took part in individual interviews that examined the impact that the Anishinabe Pride basketball program has had on their lives. The use of a talking circle was instrumental in providing a space for Indigenous voices to be heard and in confirming understanding gained through individual interviews. A separate discussion was held with Jackie Anderson, the creator of the Anishinabe Pride program, after the analysis of data to confirm results. Three themes emerged through data analysis: education, culture and community. While each theme is distinctly different, each also interconnects within the Anishinabe Pride program. Through the use of oral narrative, co-researchers shared stories and experiences of the Anishinabe Pride program and the impact it has had on their lives. It is these narratives that help define what Indigenous identity navigation looks like through the lens of the Anishinabe Pride basketball program.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".