Validation of the Applicability and Standard Revision of the Canadian Agility and Movement Skill Assessment in Chinese Children Aged 8–12
Bibliographic record
Abstract
This study aims to assess the applicability of the Canadian Agility and Movement Skill Assessment (CAMSA) in Chinese children aged 8–12 and to undertake preliminary revisions for areas found to be unsuitable. A randomized sample of 911 children aged 8–12 underwent testing. The results showed that difficulty coefficients for time scores among 8–9-year-olds were relatively low (.21–.31), while the age-related differences in skill scores for children aged 8–12 were modest (.63–.68). Significant differences were observed between high and low-scoring groups in each age category ( p < .05). Inter-rater, intra-rater and test-retest reliability ranged from r = .623 to .998 ( p < .05), all indicating moderate to strong correlations. CAMSA demonstrated a moderate correlation with TGMD-3 (r = .430, p < .05), and the Bland–Altman plot indicated a high level of agreement. Overall scores showed an increasing trend with age, with males scoring higher than females. Following standard revisions, the difficulty coefficients for time scores (.32–.65) and skill scores (.59–.73) for children aged 8–12 were found to be more suitable for the Chinese population. Meanwhile, the discriminative capacity, reliability, and validity of the assessment continued to meet the required evaluation standards. In conclusion, the CAMSA demonstrates suitability for Chinese children across discrimination, reliability, and validity, with the exception of difficulty. Following standard revisions, the CAMSA is more appropriate for use with Chinese children.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".