Guidelines for Returning to Dance Following Concussion: Adaptations From Sport Concussion Literature
Bibliographic record
Abstract
Sport concussion receives substantial attention as a public health concern. Conversely, performing artists, including dancers, sustain concussions, but these aesthetic athletes do not receive the same level of consideration nor care for this injury as that offered to traditional athletes. The concussion literature pertaining to dance is sparse, and, to our knowledge, no recommendations exist for the crucial aspect of care related to returning to dance following a concussion. The purpose of this article is to assimilate the current knowledge about post‐concussion return to activity management in sport—the closest analog of the physical demands required in dance—as a means to delineate a framework for returning to dance following a concussion. Specific guidance is provided based on a review of evidence‐based practice so clinicians can ensure that dancers return safely to both their dance activity and any academic work they are required to undertake. Concussion in dance is not an infrequent occurrence and dancers and healthcare practitioners alike will benefit from dance‐specific guidance for returning to dance post‐concussion. Overall, the principles that form the foundation for return‐to‐sport decisions are remarkably robust for application to dance.
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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 | 0.021 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".