Validity evidences of two Sports-Pedagogy-related scales: socio-educational and autonomy development in youth sports
Bibliographic record
Abstract
Abstract Competition is the essence of sports and, when conceived having participants as references, it can contributes to the development of different pedagogical contents, among them, socio-educative aspects and autonomy. The purpose of this research was to demonstrate the first validity evidences of two scales for supporting socio-educational and autonomy development in youth sports; both are part of the Battery of Tests Gonçalves-Balbinotti of Pedagogical Contents’ Development Support in Youth Sports. We aim to estimate their internal structures, test their stabilities and estimate their internal consistency. A sample of 210 coaches answered the scales related to socio-educational and autonomy development, which presented second order two-factor structures with significant factor loadings (> 0.40) and explaining 80.6% and 73.2% of the constructs’ total variance, respectively. The results related to the model fit were satisfactory (X2/df < 2.00; AGFI > 0.95; RMSEA < 0.05; CFI > 0.95; TLI > 0.95). The results regarding the internal consistency (0.786 < α < 0.913 for the factors; αSE = 0.889; αAu = 0.870) assure the precision of the measures and the reliability of their uses according to their purposes. The results answer the main and specific purposes of this research and indicate the safe use of these two scales.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".