Experiential knowledge of expert coaches on the critical performance factors of the taekwondo roundhouse kick
Bibliographic record
Abstract
The primary aim of this study was to capture expert taekwondo coaches’ experiential knowledge regarding critical factors that underpin the roundhouse kick. The secondary aim was to explore the coaching–biomechanics interface and translate the coaches’ knowledge into observable biomechanical variables for future investigation. The final aim was to elicit further expert knowledge to assess the usefulness of the resulting variables. Six higher themes emerged from interviews involving four coaches: (1) hip flexibility, (2) balance, (3) control/coordination, (4) distance, (5) footwork and (6) speed. These were supported by several sub-themes. The authors translated each theme and sub-themes into biomechanical variables: (1) front knee height, (2) support foot balance, (3) foot velocity, (4) interpersonal distance and (5) cut-kick transition speed. Two separate expert coaches appraised these variables in terms of understanding, importance, coachability and differences in expertise. In attempting to translate expert knowledge to biomechanical variables, we supported the need for a common conceptualisation of knowledge between scientists and coaches.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".