“It's a reflection of how I feel inside… of how I'm looking outside”: Racialized Young Women Athletes’ Descriptions of Body Self-Compassion
Bibliographic record
Abstract
Body self-compassion, which is a kind, non-judgmental approach to the body, may be beneficial for racialized women athletes. Racialized young women athletes may struggle with their bodies due to requirements in their sport and demands placed on the body. Researchers have found that women athletes may experience body image pressures that may lead to being preoccupied with their bodies' form and function. This could be heightened for racialized young women because of their unique bodies and the pressures to fit a majority non-racialized body ideal. Thus, a compassionate approach to the body may be particularly important to cultivating positive sport experiences for racialized young women athletes. Therefore, the purpose of this qualitative descriptive study was to explore how racialized young women athletes in Canada describe their experiences of body self-compassion. Eight racialized young women athletes (Mage = 16.63 years, SD = 1.19) engaged in two semi-structured one-on-one interviews and photo reflection. A reflexive thematic analysis was conducted, and four themes were generated: (a) Representation, diversity, and compassion; (b) Accepting my body for performance; (c) Emotions about my body and (d) Attitudes about my body. The athletes described what compassion towards the body means to them and shared their experiences of extending compassion to their bodies in sport. Despite the challenges related to having unique bodies in sport, body self-compassion could enhance resilience and foster body appreciation through developing a more adaptive and compassionate relationship with the body.
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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 | 0.012 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".