Social inclusion of people with ID from different cultural backgrounds.
Bibliographic record
Abstract
Aim: To examine social inclusion among adults with ID and to determine the extent to which it differed depending on the de?nition and measurements used. \n \nMethod: Social inclusion was measured using the following items in the interRAI ID instrument: (a) social relationships (presence of a con?dant, recent contact with family/friends), (b) participation in social activities of interest, and (c) involvement in structured activities (work, volunteer services, day programmes). Population-level data in Ontario’s institutions (1014 people assessed in 2005) and a sample of 327 community-dwelling adults (collected between 2005 and 2007) were used. \n \nResults: Social inclusion differed between persons living in institutional and community settings and within each group based on the conceptualization used. Further, there was great variability within and between groups based on the speci?c measures used within each conceptualization. For example, the rates differed greatly for the three measures of social relationships and the three measures of involvement in structured activities. \n \nConclusion: The ?ndings replicated those of other studies showing greater social inclusion among persons with ID living in community settings. The results also showed that social inclusion differed based on how the concept was de?ned, and what measurements were used to operationalize that de?nition. Findings highlight the need for a common framework for understanding and measuring social inclusion.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".