Association of Foot Deviations with Foot Functional Activity and Dynamic Balance in Female Kathak Dancers
Bibliographic record
Abstract
Kathak, an Indian Classical dance involves complex rhythmical foot work which makes Kathak dancers more prone to foot posture deviations and musculoskeletal injuries. Foot deviations can be associated with ankle and foot pain, joint and postural instability, soft tissue injuries, etc. which may negatively affect balance and dance performance. Hence current study aimed to explore association of foot deviation with foot functional activity and dynamic balance among female Kathak dancers. A cross-sectional study design 80 female Kathak dancers between age group of 18- 40 years were assessed for foot deviations, foot functional activity, and dynamic balance by Navicular drop test, foot function index, and Y balance test respectively. Percentile analysis of Navicular drop test showed that a large population of kathak dancers (56.25%) has pronated feet. Foot functional activity showed that maximum population (86.25%) didn’t have any foot function impairment. 25% population had below baseline score in Y balance test showing higher risk of losing balance and musculoskeletal injuries. Pearson’s correlation showed that Navicular drop test has very weak positive correlation with Foot Function Index with R value 0.21and has a very weak negative correlation with Y balance test with R value -0.027 and -0.03 of right & left leg respectively. Thus, current study concludes that Kathak dancers are more prone to have flat feet. Medial Longitudinal Arch Height has very weak positive correlation with foot function and very weak negative correlation with Y balance test suggesting that flat feet have very weak impact on foot function and dynamic balance. Key words: Kathak dancers, Medial longitudinal arch height, Navicular drop test, Dynamic balance, Foot function index.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".