Exploring Canadian women’s coaching journeys to high-performance sport through composite creative non-fiction
Bibliographic record
Abstract
While more women are involved in sport through leadership roles, numerous barriers continue to impede women’s sustained occupation of coaching positions in high-performance sport. Sharing women’s stories of barriers and facilitators across their coaching journeys can enhance research, practice and retention of women in meaningful coaching roles. The purpose of this study was to explore Canadian women sport coaches’ journeys in high-performance sport, using creative non-fiction. Through individual and focus group interviews, 11 women with diverse coaching backgrounds shared their coaching journeys leading to the 2022 Summer Canada Games, the largest amateur multi‐sport event in Canada. Three composite vignettes were crafted to vividly portray the participants’ shared experiences of entering and sustaining coaching roles in high-performance sport, navigating challenges as being a mother and coach, forging a better path for the succeeding generation of women coaches, and depending on a supportive community in their journeys. Recommendations are offered to help promote, support and retain women in high-performance coaching roles, leveraging creative methods, such as creative non-fiction, to amplify women’s voices.
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 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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".