INTEGRATING CHILDREN WITH AUTISM INTO THE REGULAR CLASSROOM: RECENT RESEARCH AND BEST PRACTICES
Bibliographic record
Abstract
Autism Treatment Services of Canada has identified a marked increase in the number of children who receive the diagnosis of autism, estimating as high as 20 in every 10, 000 children (1998).Such increase demands a need for services to meet the challenges of these children and their families.The goal of this project is to provide such a service by providing a manual accompanied by a web site that outlines the best teaching practices for parents and teachers of children with autism.A review of the literature examines autism, models in early intervention, integration, and strategies for teaching.Key aspects of applied behavior analysis are discussed in detail.Community resources including names of organizations, phone numbers, and web sites are included.The material is presented in a manual, web site (http://www.un1imitedmedia.calautisml.and CD-ROM.In providing such a resource it is hoped that parents and teachers can better address the needs of children with autism.IV
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".