Research needs and priorities for transition and employment in autism: Considerations reflected in a “Special Interest Group” at the International Meeting for Autism Research
Bibliographic record
Abstract
Research related to supports for adults with autism spectrum disorder (ASD) is under-developed. As an example, system and service development to support successful transition to adulthood and meaningful vocation for adults has received relatively little research scrutiny until recently, with practitioners and program developers lacking evidenceinformed approaches guiding service delivery. A Special Interest Group (SIG) was convened at the International Meeting for Autism Research in May 2014 and May 2015, with a focus on transitional and vocational issues in ASD. The SIG consisted of 120 international delegates, including self-advocates, family members, researchers, program and policy developers, practitioners, and interdisciplinary ASD trainees. Following a summary of the literature, subgroups of attendees were convened in smaller groups to identify research needs and priorities. International researchers facilitated these discussions with notes taken in each subgroup. Using a qualitative analytic approach, key themes across groups were identified. These key themes, outlined in this paper, address the identified need to (a) advance research capacity; (b) build employer capacity relative to employing persons with ASD; and (c) enhance support resources for adults with ASD and their families. Heightened research activity guiding practice and policy, community/employer engagement, and person and family-centered services were recommended. Implications for advancement and implementation are offered. Autism Res 2017, 10: 15-24. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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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 | 0.123 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".