EFFECT OF EXPERIENCE ON RATES AND RISKS OF INJURY IN RODEO
Bibliographic record
Abstract
Recent research has speculated that children have higher injury rates in rodeo than more experienced participants. We examined this question prospectively for five years, comparing incidence density and relative risk between professional rodeo contestants and novice contestants in rough stock events at 63 professional rodeos in Canada. Rough stock events include two horse riding events (saddle bronc and bareback) and bull riding. Each of these rodeos had novice and professional competitors participating in respective events. Comparison of incidence density and relative risk was made between Novice Saddle Bronc and professional Saddle Bronc contestants, Novice Bareback and professional Bareback contestants, and Boy's Steer Riders and professional Bull Riders. The definition of professional status in horse riding events requires a minimum age of 18 years or “be in the top ten of the final standings in a recognized amateur rodeo association”. Bull riding requires an 18 year minimum and “be in the top ten of the final standings of a recognized amateur rodeo association”. Novice status in horse riding events requires a minimum age of 16 years and a maximum of 21 years. Boys steer riders must be a minimum of 11 years of age and under 14 years. The incidence density and relative risk did not differ between inexperienced and experienced riders in horse riding events. The incidence density and relative risk of boys steer riders were one half that of the bull riders (1.92–3.87; RR 0.49%; CI[0.33–0.75]). Present data do not support the hypothesis that inexperienced riders are at greater risk than experienced riders in rough stock events in rodeo.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".