Self-Compassion: A Potential Resource for Young Women Athletes
Bibliographic record
Abstract
Self-compassion has demonstrated many psychological benefits (Neff, 2009). In an effort to explore self-compassion as a potential resource for young women athletes, we explored relations among self-compassion, proneness to self-conscious emotions (i.e., shame, guilt-free shame, guilt, shame-free guilt, authentic pride, and hubristic pride), and potentially unhealthy self-evaluative thoughts and behaviors (i.e., social physique anxiety, obligatory exercise, objectified body consciousness, fear of failure, and fear of negative evaluation). Young women athletes (N = 151; Mage = 15.1 years) participated in this study. Self-compassion was negatively related to shame proneness, guilt-free shame proneness, social physique anxiety, objectified body consciousness, fear of failure, and fear of negative evaluation. In support of theoretical propositions, self-compassion explained variance beyond self-esteem on shame proneness, guilt-free shame proneness, shame-free guilt proneness, objectified body consciousness, fear of failure, and fear of negative evaluation. Results suggest that, in addition to self-esteem promotion, self-compassion development may be beneficial in cultivating positive sport experiences for young women.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".