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Record W2596980990

Examining the nature and extent of hazing in Canadian interuniversity sport

2016· article· en· W2596980990 on OpenAlexaffabout
Michelle Guerrero, Jay Johnson, Margery Holman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAthletesClothingPsychologySocial psychologyMedicinePolitical sciencePhysical therapy
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the present study was to explore the nature and extent of hazing among Canadian intercollegiate athletes. A total of 358 athletes (163 males, 195 females) between the ages of 18 and 30 completed an online survey. Descriptive analyses revealed that the majority of the athletes reported that they had never been hazed (59%) and never participated in hazing others (75%) while attending their current university. The most frequently reported hazing activities included: (a) wearing clothing that was embarrassing and not part of a uniform (30%); (b) singing or chanting by oneself or with others in a public situation that was unrelated to an event, game, or practice (27%); and (c) attending a skit night or roast where other members were humiliated (17%). Athletes reported that hazing activities primarily occurred off campus (59%) and on weekends (61%). Approximately 20% of the sample believed that their coach was aware of the activities, but was not present while the activities occurred. Athletes indicated that they were more likely to talk with a friend (51%) about their hazing experiences rather than a coach (6%) or university faculty member (1.7%). Finally, athletes reported that their engagement in hazing activities made them feel more part of the team (60%). The findings shed light on the prevalence of hazing activities in interuniversity sport and the importance of creating a safe environment for student-athletes.Acknowledgments: Social Science and Humanities Research Council

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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 designObservational
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

Citations2
Published2016
Admission routes2
Has abstractyes

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