Social Norms and Concussion Disclosure Behavior: Clarification of Terms and Measurement Recommendations
Bibliographic record
Abstract
Nondisclosed sport-related concussion symptoms pose a significant risk to athletes' health and well-being. Many researchers have focused on understanding the factors affecting athletes' concussion disclosure behaviors. One of the most robust predictors of the likelihood that an athlete will disclose concussion symptoms to their coaches, athletic trainers, parents, or peers is what researchers term social norms. The extant literature regarding social norms influencing concussion disclosure behaviors is inconsistent on how the construct should be defined, conceptualized, or measured, often failing to distinguish between descriptive and injunctive social norms and their sources (direct and indirect). In this technical note, we provide an overview of these critical distinctions, their importance in assessments, and examples from the literature in which scholars have correctly operationalized these constructs in athletic populations. We conclude with a brief set of suggestions for researchers seeking to measure social norms in future research.
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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) | 0.000 | 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".