Autism spectrum disorder (ASD) specific housing supports analysis: a sequential needs analysis study in Newfoundland and Labrador in Canada
Bibliographic record
Abstract
Background: Adults with Autism Spectrum Disorder (ASD) in Newfoundland and Labrador (NL) face persistent and complex housing challenges. Despite growing recognition of neurodiversity, housing systems remain inadequately prepared to support individuals with ASD transitioning to adulthood. Fragmented policies, systemic barriers, and limited access to appropriate support services intensify these. Aim: This study aimed to explore and assess the housing needs, barriers, and preferred supports for adults with ASD in NL to inform region-specific, inclusive housing policies. Methods: Using a sequential mixed-methods approach, the study first conducted a qualitative needs assessment framed by Bronfenbrenner's Ecological Systems Theory, followed by a quantitative survey analysis guided by Bourdieu's Social Capital Theory. Data were collected from adults with ASD, caregivers, and service providers across NL's four regional health authorities. Thematic and descriptive analyses were used to study the experiences of the participants. Results: Major barriers identified in this study include social isolation, lack of independent living skills, shortage of housing options, and poor inter-agency coordination. Results of both studies showed high dependency on long-term caregiving and indicated the need for life-skills programming and support services that are specific to adults with ASD. Participants of both studies strongly recommended structured and supervised housing models that promote autonomy, while considering their needs. Conclusion: Collectively, the studies identify the urgent need for coordinated policy change, extensive support services, and housing options that are appropriate for adults with ASD. They also stress the necessity of inter-agency collaboration and recommend more research in this field to guide inclusive and sustainable housing outcomes for adults with ASD.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".