Passion Scale: Psychometric Properties and Factorial Invariance via Exploratory Structural Equation Modeling (ESEM)
Bibliographic record
Abstract
Abstract Passion is an important element among the psychological processes involved in the performance of any activity, including sports practice. Given the scarcity of nationally valid and reliable instruments, this study has the purpose of presenting the adaptation processes of the Passion Scale to the Brazilian context. A total of 789 Brazilian athletes (age:16.62±3.20; 58.4% men) participated in the study. To evaluate their psychometric properties, the scale dimensionality was estimated through the Hull method and Exploratory Structural Equation Modeling, and the accuracy by composite reliability. The factorial invariance model was estimated between men and women, and between participants of different competitive levels. Results showed the two-factor structure of the scale, according to the theoretical hypothesis, with desirable accuracy indicators. Equivalence of the measurement model was demonstrated when evaluating participants of different sexes and different competitive levels. Results suggest adequacy of the Brazilian version for the evaluation of this construct.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".