Theoretical developments in leisure studies: A look at perceived freedom and intrinsic motivation
Bibliographic record
Abstract
It was not until the 1970s that work by Neulinger, Kelly, and Csikszentmihalyi brought the constructs of perceived freedom and intrinsic motivation to the forefront of leisure research. Since then, perceived freedom and intrinsic motivation continue to be paramount in our quest to fully understand leisure studies, the conceptualization of leisure, as well as past and recent theoretical developments in leisure studies. This paper discusses how the ideas of perceived freedom and intrinsic motivation, implicit in the conception of leisure for years, have evolved through the major theoretical developments that have occurred in the field. This paper also looks at how these developments have implicated contemporary research in leisure studies, thus laying a basis for future research leading to a deeper understanding of leisure theory, practice, and conceptualization. It is concluded that, although somewhat slow, a progressive shift from social empiricism to social analysis has taken place in leisure studies research leading to the development of more recent theoretical advancements.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".