The Leisure Attitude Scale: psychometrics properties of a short version for adolescents and young adults
Why this work is in the frame
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Bibliographic record
Abstract
It is crucial to study the components of attitudes to leisure because positive attitudes tend to be associated with greater engagement in leisure. The aim of this article was to develop and validate a short version of the Leisure Attitude Scale (Ragheb M. G., & Beard, J. G. (1982 Ragheb, M. G. and Beard, J. G. 1982. Measuring leisure attitude. Journal of Leisure Research, 14(2): 155–167. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Measuring leisure attitude. Journal of Leisure Research, 14(2), 155–167) and evaluate its psychometric properties. A total of 542 adolescents and young adults participated in this study. The Leisure Attitude Scale-Short Version (LAS-SV) showed good reliability and validity. The confirmatory factor analysis presented acceptable values and confirmed the factorial structure of Ragheb and Beard (1982 Ragheb, M. G. and Beard, J. G. 1982. Measuring leisure attitude. Journal of Leisure Research, 14(2): 155–167. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it