An exploratory study examining the relationships between the leisure‐related variables and subjective well‐being of community residents
Bibliographic record
Abstract
The purpose of this study was to explore the relationships between leisure‐related variables and individuals’ subjective well‐being (SWB). This study employed the systematic random sampling strategy using 2005 Bloomington Telephone Directory. A total of 172 out of 535 households were selected in a self‐administered drop‐off/mail‐back questionnaire survey. Seventy‐seven female (49%) and 80 male (51%) residents in a small Midwestern town in the United States responded to the questionnaire. The overall response rate for the survey was approximately 30 per cent. Model fit statistics demonstrated that the relationship between leisure variables and SWB in the proposed model fit the data well. Supporting relationships is an important contribution to the leisure literature in the sense that leisure variables might have various direct and indirect effects on individuals’ SWB through leisure satisfaction. The finding of this study suggested that people who perceive leisure more positively may be more satisfied in their lives. Future research should study linkages between leisure variables and SWB from qualitative and longitudinal approaches.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".