The Leisure Attitude Scale: psychometrics properties of a short version for adolescents and young adults
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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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".