Functional Communication Profiles of Children and Youth with Autism: A Roadmap to Therapeutic and Educational Interventions
Bibliographic record
Abstract
BACKGROUND: Autism spectrum disorder (ASD) entails varied developmental pathways along the entire lifespan, demanding early and ongoing diverse and responsive interventions to children's needs. This study examined in situ education and development attained by children and youth with ASD in a school with a therapeutic and educational curriculum. OBJECTIVES: (1) Construct individual communication profiles in educational and developmental aspects. (2) Examine for associations between variables. (3) Demonstrate the clinical and educational utility of including cognitive-linguistic integrative variables. (4) Showcase how the profiles guide interventions tailored to students' individual needs. METHODS: Functional communication profiles (FCPs) of 21 students, aged 5.0-16.8 years, mostly from bilingual middle-high socioeconomic status families, were constructed with input from their educational and therapeutic staff. Students' performance was examined with an array of instruments and tasks, including person and clock drawings, false belief, and bouba-kiki metaphor screens. Qualitative and quantitative analyses were performed to uncover associations, weaknesses, and strengths. RESULTS: The profiles revealed associations between cognitive, linguistic, social, and educational abilities, indicating that some abilities from different domains tend to co-occur. CONCLUSIONS: Including cognitive linguistic integrative variables was a novelty that revealed additional aspects of the children's abilities. Staff feedback confirmed the utility of FCPs in providing "a roadmap" to needed individual and common curriculum adjustments.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".