Bibliographic record
Abstract
The Canadian sport system is challenged by the lack of representation of female leaders and coaches. This is, in spite of statistics showing that female athletes account for almost half of all participants in sport, a number that is still growing (Sport Canada, 1999). Women have acquired equity in many areas of life and are accepted in leadership roles, however in the area of sport, women have yet to gain the full credibility and professional respect equal to their male counterparts. Previous research indicates that women who pursue a career in coaching face many adversities and struggle to attain a level of leadership where they can achieve their highest potential (Acosta & Carpenter, 2002). The purpose of this research is to gain an understanding of the lived experiences of elite female coaches, using Erikson’s (1950) theory of psychosocial development. In this study, the qualitative method of life history was used to learn about the experiences of female coaches, specifically the process of becoming and being elite coaches. Five elite Canadian coaches were interviewed. The major themes that developed through the analysis of the interviews were: (a) Support, (b) Overcoming Obstacles, (c) Personal Qualities and (d) The Bigger Picture. The study noted the importance of various support systems through one’s lifespan and some of the challenges a female athlete and coach must overcome to become a successful athlete, coach and mother. The study shares insight into the five women’s personal qualities that helped them grow into elite coaches. Finally, the participants described the process by which they came to find a leadership style with which they were comfortable, as coaches and as women.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".