Les tâches professionnelles et la satisfaction au travail des intervenants en loisir œuvrant en milieu institutionnel québécois
Bibliographic record
Abstract
This study examined the job duties and job satisfaction of stakeholders working in the 350 leisure facilities affiliated with the Fédération québécoise du loisir en institution. The sample included 159 respondents including recreational therapists, community recreation technicians, or special education technicians. The average age was 42 years and 77% of respondents were women. Factor analysis of the tasks identified four factors: (1) administration, (2) therapy, (3) animation, and (4) development. Factor analysis performed on the simplified version of the Minnesota Satisfaction Questionnaire confirmed the extrinsic or intrinsic dimensions generally attached to this measurement instrument. In addition, a canonical analysis was conducted to determine the relationship between the categories of professional tasks, job satisfaction, and certain demographic variables. The results indicate that the stakeholders engaged more in recreational therapy, administration, development, and less in animation-related tasks were recreational therapists, with higher wages, and higher expressed extrinsic satisfaction. In addition, stakeholders doing fewer administrative and animation-related tasks and more therapeutic tasks did not work in a care facility and showed less intrinsic satisfaction. This study points to several practical implications for professional associations, training program managers, and researchers wishing to better understand the professional reality of stakeholders in therapeutic recreation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".