Dodgeball: Inadvertently teaching oppression in physical and health education
Bibliographic record
Abstract
Though students can learn a great deal about ethics as they play sport, the authors of this article ask what, exactly, they learn from playing dodgeball. As they look beyond the usual arguments offered for and against the teaching of the game, they view it through three ethical lenses: the ethic of care, the ethic of anti-oppressive education, and the ethics of virtue. They conclude that in terms of modelling, confirming, and practising caring behaviours, or offering opportunities to discuss and process what might be considered fair, dodgeball can be considered miseducative. They further argue that the hidden curriculum of dodgeball reinforces the five faces of oppression defined by the feminist theorist Iris Young as marginalization, powerlessness, and the helplessness of those perceived as weaker individuals through the exercise of violence and dominance by those who are considered more powerful. They conclude that the playing of dodgeball habituates the practice of aggression and fails to contribute positively to an ethical education.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".