Autism and Autism Services with Indigenous Families and Children in the Settler-Colonial Context of Canada: A Critical Scoping Review
Bibliographic record
Abstract
In Canada, Indigenous families and children experience structurally-rooted marginalization due to longstanding and ongoing histories of colonization and discrimination. Indigenous children with autism spectrum disorder (ASD) are currently underrepresented in literature and databases on ASD in Canada, raising concerns about their equitable access to related services and optimal health outcomes. This critical scoping review maps out existing and emerging themes in literature pertaining to ASD and the provision of ASD services with Indigenous children and families in Canada. No previous reviews of literature have focused exclusively on ASD among Indigenous children in Canada. A literature search conducted across eight databases between 2011 and 2021 resulted in 362 potentially relevant publications, of which 19 met our inclusion criteria. Findings point to a clear lack of data on ASD and unmet health, social, and educational service needs among Indigenous children with ASD in Canada. ASD is also frequently discussed through a Western, deficit and medical discourse. The main contributors to the lack of data and unmet service needs relate to the historical positioning of colonial oppression, stigma, an overrepresentation of fetal alcohol spectrum disorder (FASD), lack of funding, and concerns about standardized diagnostic and assessment tools, and social determinants of health. Recommendations for policy, practice and research concerning Indigenous children with ASD are proposed.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.019 | 0.029 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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".