Leisure in later life for people with intellectual impairments: beyond service provision toward person coherence
Bibliographic record
Abstract
Rooted in a paradigmatic history of institutionalization and dependency, leisure professionals have assumed that without intervention, retirees with intellectual impairments may experience loneliness, isolation, and inactivity when leaving the structured settings of sheltered employment. The belief that expert-driven programs are necessary to live active, engaged, and meaningful retirements reflects an enduring deficits-based discourse of disability. The purpose of the study was to understand the experiences of three men with intellectual impairments who enjoyed self-directed active leisure in retirement without professional supports or constraints of recreation and leisure specialists. Using narrative inquiry methodology the inward experiences of places that supported autonomous retirement leisure were uncovered; the senior centre, rural connections, downtown, and church. Their stories illustrated rejection of the professional landscape of expert-driven leisure programs by composing self-directed leisure activities interconnected with their past interests, preferred social networks, and place. Their narratives disrupted beliefs that professionally crafted programs are necessary for a satisfying, active, and engaging retirement. An alternate paradigmatic lens of personal coherence emerged reflecting self-driven expressions of leisure based upon personal history, autonomy, and choice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".