Resilience and professionalism in the face of racism: Exploring the experiences of First Nations Canadian sport coaches
Bibliographic record
Abstract
The Truth and Reconciliation Commission of Canada's (2015, p. 10) Call to Action #89 urges the Government of Canada to: amend the Physical Activity and Sport Act to support reconciliation by ensuring that policies to promote physical activity as a fundamental element of health and well-being, [. . .] and build capacity in the Canadian sport system, are inclusive of Aboriginal peoples. The lived experiences of Indigenous sport leaders, such as coaches, can greatly inform such initiatives, yet a noted lack of Indigenous coaches in Canada (Canadian Heritage, 2005) raises question as to the factors influencing Indigenous coaches' coaching paths. To date there has been limited research in this area, although work in Australia highlighted several factors, including racism (Bennie et al., 2019). Following Wilson's (2001) Indigenous research paradigm and using a socioeconomic model based on the work of Bronfenbrenner (1977), this research roughly mirrored that of Bennie et al. (2019). We engaged 10 First Nations Canadian sport coaches in conversations regarding the facilitators and barriers they experienced along their coaching paths. This presentation specifically focuses on racism, providing insight into how the coaches interviewed dealt professionally with this challenge during their coaching careers. The results of this research can be helpful to other First Nations coaches, as well as to organizations seeking to address racism in sport so as to encourage more respectful environments for First Nations coaches and, as a result, athletes.Acknowledgments: Gratitude is expressed toward all study participants, the CD Howe Memorial Fellowship program, SSHRC, the Sport Canada Research Initiative, and the Vanier Canada Graduate Scholarship program
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.049 | 0.028 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".