The Creation of an Individualized School Plan for Optimal Inclusion of Students with Osteogenesis Imperfecta
Bibliographic record
Abstract
AIMS: The aims of this study were to: (1) synthesize existing evidence regarding the integration of students with osteogenesis imperfecta (OI) into the school setting, (2) tabulate existing school integration tools for OI, and (3) create an individualized school plan to facilitate school integration. METHODS: Guided by the process of developing evidence-informed guidelines, an international, interprofessional, expert task force was convened. The process entailed: (1) reviewing of the literature, (2) developing recommendations, and (3) creating a clinically meaningful, person-focused plan to facilitate the integration and promotion of school inclusivity. The 13-member task force relied on empirical studies, grey literature, and their experiential knowledge (from clinical, teaching or patient experiences) to devise the plan. RESULTS: Over a series of eight meetings and five drafts, the Task Force prioritized 14 core items for inclusion. These items consisted of general student information, fracture response protocol, student inclusion recommendations, mobility considerations, transfer considerations, toileting protocol, physical education recommendations, fieldtrip information, transportation considerations, evacuation plan, environmental and scholarly considerations, consent and authorization, and an annual renewal document. CONCLUSION: Further research is recommended to pilot the plan, solicit ongoing feedback, implement and evaluate the plan into routine education and health care practices.
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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 | 0.041 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".