Diverging from Conventional Autism Research Through Meaningfully Including an Adult Autism Community: Processes of Engaging Ottawa’s Adult Autism Community in Critical and Emancipatory Autism Research
Bibliographic record
Abstract
Traditional research practices that aim to find causes, cures, and fixes for autism, without meaningful involvement of Autistic individuals, undermine disability justice and the inherent value of the Autistic perspective and Autistic contributions to society. Limited studies address the process of inclusive research and upholding disability justice principles; therefore this paper presents the process of a participatory planning stage for a research study committed to disability justice and social change for Autistic people. Drawing from the principles of disability justice, including intersectionality, leadership, anti-capitalism, cross-movement organizing, and collective liberation, the paper outlines both the successes and obstacles encountered during the planning stage. Through methods such as participant observation, documentary research, and unstructured interviews, this paper displays the process of actively engaging Ottawa’s adult autism community in the development and execution of research, promoting community priorities and fostering meaningful inclusion strategies. It contributes to the advancement of disability justice and emphasizes the importance of centering the voices and agency of Autistic individuals in research endeavors. By including the adult autism community in a meaningful way, this research diverges from conventional autism practices by engaging Ottawa’s community in critical and emancipatory autism research.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.040 | 0.044 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.003 | 0.005 |
| 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".