The Value of Caregiver Time: Costs of Support and Care for Individuals Living with Autism Spectrum Disorder
Bibliographic record
Abstract
WHY IS THIS AN IMPORTANT ISSUE?An estimated 1 in 86 children are diagnosed with Autism Spectrum Disorder (ASD)1 making it the most commonly diagnosed childhood neurological condition in Canada.2 The true costs of lifelong support for people living with ASD3 are often underestimated and fail to acknowledge the value of caregiver time over the lifespan. Significant gaps in publically provided support systems leave the cost burden to be picked up by families. Relying on continued family supports where community services are fragmented or unavailable is not a sustainable approach. WHAT DOES THE RESEARCH TELL US? A continuum of supports are needed Most people living with ASD need supports that range from occasional assistance with higher level tasks, like organizing appointments or banking, to those who need continuous help with daily living.4 Areas where supportive care may be needed can be categorized broadly to include: self care, home living, service co-ordination, personal organization, health and safety management, adult day opportunities/employment, transportation, advocacy and social skills. These supports are most successful when they address the individual’s uniqueness in terms of communication, social, sensory, behavioural needs and physical and/or mental health conditions. Currently there are a lack of available supports, limiting opportunities for socialization, employment and residential living resulting in reduced independence 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 | 0.018 |
| 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 | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".