Nonviolence and Catholic school sport: recommendations for supporting mission as drawn from a historical case study
Bibliographic record
Abstract
For centuries, Catholic schools have promoted extra-curricular activity as a means to develop well-rounded students. Sports programming has been a vital aspect of this work, but there is little research into how these programmes can support the combined educational-religious missions of the schools. In response, this paper relies on archival and interview research to present a historical case study of Canadian coach-educator Father David Bauer, who spent his lifetime as a Basilian priest educating through sport in the face of its violent tendencies. We discuss how Bauer, as an educator and prominent international figure in ice hockey, identified difficulties arising from violence over several decades. Influenced by his military experience and his religious community’s educational charism, we see how Bauer drew from a Basilian intellectual tradition and other experiences to push back against several types of violence arising in sport: physical, psychological, structural, media-driven, and others. The paper concludes with seven recommendations of nonviolence for Catholic school sports programmes, where leaders can learn from Bauer’s story and enable programmes of human development and bridge-building, and thereby, positively enhance school mission.
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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 | 0.023 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.032 | 0.033 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".