A Five‐Country Comparative Review of Accommodation Support Policies for Older People With Intellectual Disability
Bibliographic record
Abstract
Abstract International covenants and domestic social policies in most developed countries regard people with intellectual disability as citizens with equal rights, suggesting they should have the similar aspirations of a healthy and active old age as the general community, and an expectation of the necessary supports to achieve this. This article compares the development and implementation of accommodation support policies for people aging with intellectual disabilities in five liberal welfare states. It describes the limited development of policies in this area and suggests possible reasons why this is the case. A review of the peer reviewed and grey or unpublished advocacy and policy literature on aging policies for people with intellectual disability was conducted which covered Australia, Canada, Ireland, the UK, and the U.S. Despite consistent identification of similar broad policy issues and overarching goals, little progress has been made in the development of more specific policies or implementation strategies to address issues associated with accommodation support as people age. Policy debates have conceptualized the problem as aging in place and the shared responsibility of the aged‐care and disability sectors. This may have detracted from either sector leading the development of, or taking responsibility for, formulating, implementing, and resourcing a strong policy framework.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".