“It’s hard to define and really hard to implement”: Competitive women athletes’ descriptions of self-compassion.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research on self-compassion as an important resource for women athletes is increasing at an impressive rate. However, there can be misunderstandings about what self-compassion is and is not. This is perhaps not surprising given that self-compassion is not part of most athletes’ common vernacluar. The best language to use when talking about self-compassion with women athletes remains unclear. The purpose of this qualitative description study was to explore women athletes’ understandings of self-compassion, particularly their language used to describe the construct. Competitive women athletes (N =19; Mage = 22.6 years, SD = 5.4) were invited to participate in two phases of virtual focus groups. Phase 1 generated information regarding women athletes’ descriptions of self-compassion. Elo and Kyngäs’ (2008) content analysis was used to prepare, organize, and report the data into content-specific themes. Preliminary themes were shared with participants in Phase 2 (11 of the original 19 participants returned), after which all focus group transcripts (i.e., Phase 1 and Phase 2) were (re)analyzed using the same analytic approach. Three themes were generated: (a) Show up (driven by empowerment, supporting myself as I support others), (b) Regroup (honestly checking in with myself for real expectations), and (c) Trust (trusting the process and trusting myself). The language used by participants to describe self-compassion incorporates elements of both tender (i.e., comforting reassurance) and fierce (i.e., protecting and providing) forms of self-compassion. Findings provide relevant and useful information for researchers, applied practitioners, and sport personnel seeking to communicate with women athletes about self-compassion.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it