Online youth concussion resources for Canadian teachers and school staff: A systematic search strategy
Bibliographic record
Abstract
INTRODUCTION: Teachers and school staff (i.e., principals, coaches, trainers, educational assistants, guidance counselors, school healthcare professionals, etc.) are well positioned to support students' return-to-school post-concussion. Teachers and school staff may access concussion resources online as they are readily available; however, their quality and accuracy are unknown. OBJECTIVE: To identify accurate online concussion resources suitable for Canadian teachers and school staff. METHODS: A five-phased systematic search strategy was conducted: 1) initial identification of resources; 2) consultation of pediatric concussion experts; 3) inclusion and exclusion criteria; 4) content review; and, 5) material evaluation. RESULTS: A total of 837 resources were identified initially and 40 resources were included in the final list. Across all resources, 310 (37%) resources were excluded as they were not designed primarily for teachers and school staff. Thirty-four (43%) of 80 resources reviewed for content accuracy were excluded. Among resources reviewed for readability, usability and suitability, six (13%) were excluded. CONCLUSIONS: The 40 resources identified in this study can enable teachers and school staff to educate themselves about concussion and how to optimally support a student's return-to-school post-concussion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".