Can 16–18-Year-Old Elite Ballet Dancers Improve Their Hip and Ankle Range of Motion Over a 12-Month Period?
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of a 12-month intensive ballet training regimen on hip and ankle range of motion in male and female, first- and second-year professional dancers. DESIGN: 12-month longitudinal follow-up. SETTING: National classical ballet school in Australia. PARTICIPANTS: 28 female and 20 male full-time ballet students with a mean +/- 1 SD, ages 16.8 +/- 0.8 and 17.7 +/- 1.2 years, respectively. MAIN OUTCOME MEASURES: Degrees of range of motion of left and right sides for the following movements: standing plié in parallel-passive ankle dorsiflexion (DF); standing turnout in the balletic first position--lower leg external rotation (LLER); supine hip external rotation (ER); supine hip internal rotation (IR). An additional range of motion was calculated: external rotation below the hip joint (BHER) derived by subtracting hip ER from LLER. MAIN RESULTS: In all subjects combined, hip and ankle ranges increased statistically on the right. However, the amount was generally minimal and most at the borderline of the amount of error associated with the measurement tool. While there was no change in LLER, there was a decrease in BHER. There were no overall gender differences, and year differences existed only for left hip ER and total hip ER with first-year dancers showing significant improvements in these ranges. For DF and sum of hip IR, first-year males and second-year females had increases in range. There was a negative relationship between baseline range and the amount of change over the 12 months. CONCLUSIONS: Dancers ages 16-18 years who enter full-time ballet training did not augment their ankle dorsiflexion to any appreciable degree. Some, but certainly not all, increased their hip active external rotation over 12 months without increasing their total lower limb turnout. Hip ER was more likely to improve in the first-year rather than second-year student in this elite full-time training school.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".