An evaluation of quality participation experiences in the inclusion resource team program for individuals who have an intellectual disability
Bibliographic record
Abstract
Individuals who have an intellectual disability (ID) face several barriers to community recreation, including a lack of suitable programs and social support. To address these barriers, the City of Mississauga and Community Living Mississauga (Ontario) developed the Inclusion Resource Team (IRT) program. This pilot program involves a one-on-one service delivery model where adults who have an ID are given the opportunity to engage in any recreation program offered by the City with the support of an inclusion facilitator. This study explored the participation experiences of IRT participants, caregivers, and staff. Participants (n=4), caregivers (n=6) and staff (n=21) took part in semi-structured interviews or focus groups to obtain program provider and end-user perspectives. A deductive thematic analysis was conducted using the six building blocks of quality experiences (autonomy, belonging, challenge, engagement, mastery, meaning) and environmental conditions (social and physical environment, activity characteristics) adapted from the Quality Participation Framework. Positive program experiences were discussed regarding participants' enhanced sense of autonomy, challenge, mastery, and meaning. Mixed experiences, however, were discussed for belonging and engagement. These experiences were often influenced by activity type, program size, and perceived quality of one-on-one support provided. Specifically, individually-focused activities with small class sizes and positive relationships with knowledgeable staff fostered a greater sense of engagement and belonging. Results will be used to refine the IRT program to increase the quality of community recreation experiences among adults who have an ID. These findings can also be used by other municipalities to develop inclusive recreation opportunities that foster quality participation.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".