What makes life better or worse: Quality of life according to people with intellectual disabilities
Bibliographic record
Abstract
BACKGROUND: People with intellectual disabilities are rarely involved in research on quality of life. The study sought to answer the question: what do people with intellectual disabilities believe improves or hinders their quality of life? METHOD: Using an inclusive, accessible research design, 18 participants met in small groups to answer the study's question using their choice of arts-based media. Participants completed the analysis collaboratively, identifying key themes among their responses. RESULTS: The participants concluded that supports, well-being, hobbies, and activities contribute to quality of life. Lack of accessibility, assumptions, negative behaviours, stress, and negative people (staff, roommates, people in general) were identified as detractors of quality of life. CONCLUSIONS: To continue to make progress in improving the quality of life of individuals with intellectual disabilities, the voice of those with intellectual disabilities is key. The results suggest key areas of focus to make these improvements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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 teacher head, 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".