Building <i>Bridges to Housing</i> for homeless adults with intellectual and developmental disabilities: outcomes of a cross‐sector intervention
Bibliographic record
Abstract
BACKGROUND: Adults with intellectual and developmental disabilities (IDD) have high rates of homelessness. This observational study evaluates Bridges to Housing, a cross-sector intervention offering immediate access to housing and supports to this population in Toronto, Canada. METHODS: Twenty-six participants, enrolled between April 2016 and December 2017, were assessed at baseline, six and 12 months post-enrolment. Descriptive statistics and generalized linear modelling evaluated quality of life (QOL) and service needs outcomes. Twenty-one service users and providers participated in semi-structured interviews between August 2017 and June 2018 to elicit their experiences of the intervention, which were analysed thematically. RESULTS: (2) = 12.93, p = .002). Individual-, intervention- and system-level characteristics facilitated housing stability in this population. CONCLUSIONS: Cross-sector approaches can improve outcomes for homeless adults with IDD and may have an important role in supporting this marginalized population.
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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 | 0.002 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".