Risk, Responsibility, and Prevention in Injury Management: Implications of Concussion (mis)education on Youth Athlete Knowledge Uptake
Bibliographic record
Abstract
Concerns over the short- and long-term health implications of concussions has led to a surge in concussion education materials, resources, and modalities to educate youth athletes as a first line of defense in injury prevention. In this paper, we argue that this over-emphasis on concussion education–and a reliance on static, sensationalized, and culturally disconnected messaging–fails to consider the sociocultural implications of concussion education and the subsequent uptake and impact of this information by/on youth athletes. To do so, we present research involving semi-structured interviews with youth athletes in Ontario, Canada ( N = 28; aged 13-18-years-old) focused on understanding experiences with concussion knowledge and education. Through our analysis, we highlight three important domains related to athletes’ experiences with concussion education concerning (1) sufficient education, (2) scare tactics in education efforts, and (3) equity, access, and responsibility. By problematizing education as an effective mode of injury prevention, we draw attention to a gap within current sport-related concussion literature concerning knowledge uptake, education, and behaviour with the social and cultural realities of concussion experiences.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".