Translation and Validation of the Canadian Assessment of Physical Literacy for Polish Children Aged 8–12
Bibliographic record
Abstract
Purpose: This study aimed to culturally adapt and validate the Canadian Assessment of Physical Literacy for use with Polish children aged 8–12 years. Method: The Canadian Assessment of Physical Literacy questionnaire was translated into Polish and adapted using the method of forward and back translation. The internal consistency, reliability, and construct validity were examined ( n = 781). Results: The motivation and confidence domain demonstrated excellent internal consistency (α = .876) and test–retest reliability (intraclass correlation coefficient = .905), while the knowledge and understanding domain showed moderate reliability (α = .70; intraclass correlation coefficient = .714). Confirmatory factor analysis results, χ 2 (37) = 72.7, p < .001, χ 2 /df = 1.95, comparative-fit index = .982, Tucker–Lewis index = .973, root mean square error of approximation = .031, standardized root mean square residual = .024, supported the four-domain model as a good fit for the data. Discussion/Conclusion: Overall, the findings confirm that this Polish version of Canadian Assessment of Physical Literacy is a reliable and valid tool for assessing physical literacy among Polish children across all four domains.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".