Au niveau international, quelles sont les fonctions d’un plan d’intervention (PI) ou de transition (PT)?
Bibliographic record
Abstract
More than 45 years of IEP/TP research and a few focused on IEP/TP functions or roles. Yet, \nthe quality of an IEP/TP relies on the functions that it fulfills to satisfy the needs of its different users (Petitdemange,1985). The Quebec Ministry of Education (MEQ, 2004) and the \nOffice of Special Education and Rehabilitative Services within the U.S. Department of Education (in Eichler, 1999) explicitly identified and described six to seven IEP/TP functions. \nHowever, a literature review and practising environments highlighted a greater number of \nfunctions. The goal of this research is to identify the different functions that an IEP/TP \nshould fulfill in regard to the different needs of its diverse users. With the use of pedagogical \nvalue analysis method (PVA), results show a synthesis of more than 700 functions organized \nin an IEP/TP Functional Specification Matrix (FSM). The IEP /TP FSM is useful to create, \nmonitor and evaluate IEP/TPs
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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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".