Reflections on Improving Women’s Experiences of Mentorship in Canadian Coaching
Bibliographic record
Abstract
Despite recent advancements for women in leadership roles, women remain underrepresented in sport coaching contexts. Mentorship has been advocated as a potential avenue for advancing and sustaining the careers of women coaches. In line with this, national sporting bodies have implemented mentorship programs to pair new and aspiring women coaches with senior leaders. While recent evaluations show promising results, research is needed to understand how these programs are conceptualized, implemented, and experienced by program participants. The purpose of this study was to qualitatively explore stakeholders’ experiences in two Canadian women in coaching mentorship programs. Perspectives were gathered from 21 Canadian sport stakeholders that included program mentees, mentors, and staff. Data were analyzed using a reflexive thematic approach. Findings demonstrate the need for purposefully recruiting both mentor and mentee coaches to sustain meaningful partnerships. Additionally, participants highlighted the need for sport organizations to situate women in coaching as a priority and engage in sponsorship and long-term planning for sustaining women’s advancements in coaching. This study explores women in coaching mentorship programs from multiple perspectives, which may inform future formalized mentorship opportunities for women coaches by addressing identified challenges and barriers.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.055 | 0.015 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".