Using Social Cognitive Theory to predict hazing perpetration in athletics
Bibliographic record
Abstract
Hazing has been defined as "any activity expected of someone joining a group that humiliates, degrades, abuses or endangers, regardless of the persons willingness to participate" (Hoover, 1999, p.8). Despite the potential seriousness of hazing activities, very few studies have examined hazing from a theoretical perspective, particularly within the context of athletics. The purpose of the present study was to utilize Social Cognitive Theory (Bandura, 1986) to predict the perpetration of hazing behaviour, with a particular focus on select personal and environmental factors. Participants included 338 athletes from 27 sports teams at seven Atlantic Canadian universities. Participants completed questionnaires related to personal factors (moral disengagement, rookie experiences with hazing, attitudes toward hazing, gender) and environmental factors (team size, degree of physical contact) were also measured. The results indicated that the personal and environmental factors included in the model significantly predicted the self-reported perpetration of hazing behaviours, accounting for nearly 50% of the variance in the dependent variable. The personal factor, experiences with hazing as a rookie, was found to be the most powerful predictor of hazing experiences as a veteran suggesting that hazing victimization leads to a higher rate of hazing perpetration. Other significant predictors included proneness for moral disengagement, attitudes about the purpose of initiation, gender and the degree of physical contact in the sport. The broader theoretical and practical implications of these findings are discussed in detail.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".