Practices for Sport-Coach Mentorship: A Historical Case Study for Coaches in Catholic Schools Today
Bibliographic record
Abstract
Sport-coach mentorship is perhaps the raison d’etre for the inclusion of sports programming within Catholic schools. Coach-educators can have significant and even lifelong impact on student-athlete growth and development. But, how, exactly, should coaches act as mentors in faith-based, educational contexts? Drawing upon an extensive archival and interview research project, this paper presents a historical case study of the sport-coach mentorship of Father David Bauer, csb (1924-88), an educator and exceptional Canadian ice hockey player, coach, manager, and Hockey Hall of Fame inductee. Bauer mentored and spoke out for young sportspeople over many decades. The first part of this paper provides background about Bauer, the priest-coach, highlighting his relationships with his religious community, family, and sporting colleagues and players, all of which guided his model for mentorship. The second part unpacks how Bauer’s approach to sport-coach mentorship follows a leadership style that is humanistic, relational, developmentally appropriate, critical, and faith-based, among other qualities. Based on stories, speeches, and events, seven practices for mentorship emerge. These practices reveal how Bauer challenged assumptions and systems within the sporting world and they also establish an approach to youth sport-coach mentorship that can enlighten and guide Catholic school coaches today, in particular, as well as athletic directors and other sport leaders, in general.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".