Bibliographic record
Abstract
UNLABELLED: The purpose of the present study was to examine chiropractic utilization following a sport-related injury among National Team members and other high level Taekwondo athletes. METHODS: Retrospective surveys were conducted among Canadian male and female Taekwondo athletes (Group A, n = 60) competing in a national tournament and National Taekwondo team athletes (Group B, n = 16) at a training camp. RESULTS: A response rate of 46.7% (Group A) and 100% (Group B) was achieved. Twenty five percent (n = 4) of Group A athletes reported never seen a doctor of chiropractic (DC) regarding their injuries. Over 12% (n = 2) reported visiting a DC often, while just over 6% (n = 1) reported that they usually visited the DC following an injury. When injured, over 36% (n = 7) of the National Team members visit their family physician, over 15% (n = 3) visit a chiropractor or physiotherapist and the remaining athletes (n = 6) equally visit osteopaths, massage therapists, or athletic therapist following an injury. CONCLUSION: There is a lack of information surrounding chiropractic utilization in the majority of sports and minimal research published regarding the health care utilization of Taekwondo athletes. Chiropractors, and particularly those with extensive athlete contact, should endeavour to further utilization studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".