“I am strong, I am fast, I am powerful”: a creative art-based application of body self-compassion with racialised young women athletes in Canada
Bibliographic record
Abstract
Body image is a multidimensional construct that influences body-related self-attitudes and self-perceptions. Racialised (i.e. persons of colour) young women athletes have unique body-related experiences that may impact their body perceptions in sport. Body self-compassion, a kind and non-judgemental way of approaching one’s body experiences, appears relevant for racialised young women in sports. The purpose of this narrative study was to explore an art-based application of body self-compassion with racialised young women athletes. Seven racialised young women athletes (Mage = 15.14 years, SD = 2.12) participating in a variety of sports engaged in focus group discussions and body mapping. A dialogical narrative analysis was conducted, and three narrative themes were generated: (a) Between worlds: Compassionate accounts of the racialised body; (b) The Importance of others in Compassionate Support; and (c) Faith and culture in sport: A journey of belonging and meaning. To communicate the findings in a way that engages readers and deepens understanding of the athletes’ lived experiences, creative non-fiction was used. The findings are represented through five portrait vignettes and reveal that body self-compassion can foster a focus on function (i.e. what the body can do versus its appearance), particularly for athletes navigating the intricate intersections of race, culture, and religion. This study contributes to the evolving discourse on the sport experiences of racialised young women athletes, advocating for a more inclusive and compassionate approach that honours the complex intersections of their identities.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".