THE USE OF APPLIED BEHAVIOURAL ANALYSIS IN TEACHING CHILDREN WITH AUTISM
Bibliographic record
Abstract
(IEIP) is a program funded by the province of Ontario. It is used to teach/treat young children who have been formally identified as having an autistic spectrum disorder. Intensive Behavioural Intervention (IBI) services are provided to these children, aged 2 to 5 years, who meet specific program requirements. The program was designed taking into consideration the central tenets of Applied Behavioural Analysis (ABA), which is a widely recognized and accepted method for teaching functional skills to children with autism. In this paper, we review the effectiveness of Intensive Behavioural Intervention for teaching/treating young children with autism. The effects of age, duration of therapy, and number of hours of therapy are examined in an effort to determine whether or not there would be an increase in the participants ’ IQ, adaptive functioning, and language abilities after receiving intensive services from the program. With reference to this, data on three children with autism are presented in an attempt to isolate and
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".