The Closeness of Fit: Towards an Ecomap for the Inclusion of Pupils with ASD in Mainstream Schools
Bibliographic record
Abstract
The number of pupils with autism spectrum disorder (ASD) who join mainstream schools in the UK has been increasing over the last decade. Given the difficulties in social and emotional understanding which these children have, their inclusion in schools is likely to be challenging. Their ASD-related manifestations, moreover, tend to allow for tensions to arise between them and the different systems of the school ecology. We examine the inclusion of these pupils from a developmental-systems perspective as articulated by the bio-ecological and the transactional models. Using data from a qualitative research project which explored the effect of autism-related difficulties in social and emotional understanding on the inclusion of 17 pupils with ASD the study describes the working dynamic of the arising tensions at the micro-system level. The study outlines an ecopmap of the nested structures at the micro-, meso-, exo-, macro- and chrono-systems which may facilitate or impede the children’s 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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".