Possible educational implications of the underdiagnosis of autism spectrum disorders, ASDs, of aboriginal children in British Columbia, Canada
Bibliographic record
Abstract
During a preparational trip to Vancouver, Canada, to come in contact with possible participants for my PhD study about the meaning of music for aboriginal children diagnosed with autism spectrum disorders, ASDs, local researchers and school officials informed me that there are very few known cases in British Columbia, BC. Canada. Furthermore it seems that researchers have limited access to this field. The aim of this review of publications on the prevalence of autism, ethnicity and aboriginal groups is to get an overall picture of previous research and possibly contribute with insights that can be useful in understanding the situation in BC. It is also the starting point for my fieldstudies. The review reveals that aboriginal children in BC, Canada are underdiagnosed and underrepresented in research context. Possible reasons can be cultural, ethnical, diagnostic substitution, symptoms being recognized as schizophrenia, or ethnic bias in diagnostic decisions and the impact of historical oppression and discrimination. If aboriginal children in fact are underdiagnosed with autism, the educational implications may be severe, individually, but also as a minority group. They are also missing the opportunity to get funding provided by the B.C Ministry of Children and Family Development for families to purchase treatment and intervention for children up to 18 years of age. One of the characteristiscs of autism is the need for sameness and disruptions often lead to eruptions, outbursts or undesirable behavior. Positive effects on social and classroom behavior have been seen in research regarding music interventions for children with ASDs but music as an educational/special educational tool for inclusion has yet to be investigated. In the academic year 2013/2014 I intend to do ethnografic fieldwork on the meaning of music for aboriginal children with ASDs and screening for autism in children from indigenous communities in BC, Canada, as two studies towards my dissertation. Possibly accurate assessment of ASDs within the aboriginal community and learning about the use and qualities of indigeneous music within this population can give us the opportunity to transform educational practice and facilitate inclusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".