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Record W4319047306 · doi:10.1080/19422539.2022.2162908

Nonviolence and Catholic school sport: recommendations for supporting mission as drawn from a historical case study

2023· article· en· W4319047306 on OpenAlexafffundabout
Matt Hoven

Bibliographic record

VenueInternational Studies in Catholic Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsThe King's UniversityUniversity of Alberta
FundersSexually Transmitted Infection Research FoundationUniversity of Alberta
KeywordsSociologyFace (sociological concept)Physical educationPedagogyPublic relationsPsychologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.113
GPT teacher head0.496
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes3
Has abstractyes

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