Social Work Practice in Autism and Intellectual and Developmental Disabilities
Bibliographic record
Abstract
In Canada, social work—both the profession and the academic discipline—has given inadequate attention to individuals living with autism and intellectual and developmental disabilities. This is true regardless of whether the social work role is in a clinical capacity, community-based programs, academic research and educational endeavours, or an advocacy role or supporting self-advocacy for basic needs and rights to services and supports. Many people with autism and intellectual and developmental disabilities, and their supporters, value community involvement and integration, quality of life, and access to a wide range of services, so it is likely that social workers will encounter these clients in their careers. Consequently, the onus is on the social work profession to attend more fully and carefully to preparing students, practitioners, and researchers. This peer-reviewed volume provides a range of perspectives, practices, and ideas relative to social work’s engagements with individuals living with autism, intellectual disabilities, and developmental disabilities. Contributors include social work practitioners, academic and community-based researchers, educators, activists, and self-advocates. Reflecting different ways of theorizing, speaking about, and working with people with autism, intellectual disabilities and developmental disabilities, it explores both tensions and possibilities for social work practice, research, education, advocacy, and policy development that better meet their needs and desires for their lives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".