Children with Acquired Brain Injury: A Silent Voice in the Ontario School System.
Bibliographic record
Abstract
The leading cause of death and injuries in school age children is acquired brain injury (Savage & Wolcott, 1994). Each year approximately 1 in 450 school age children and 1 in 200 adolescents/young adults suffer an injury as a result of some form of acquired brain injury. Approximately 27,000 students in the Ontario school system have acquired brain injury (Segalowitz & Brown, 1991). For these students accessing support services for educational purposes can be a challenge. Within the province of Ontario, there currently exist five categories within which students can be identified as exceptional, however acquired brain injury is not included within these five. Furthermore, regular classroom teachers are rarely provided with any training at either the preservice level or at the practicing level that addresses the educational need of children with acquired brain injury. Therefore, children with acquired brain injury are usually poorly identified and understood in the educational system leading to inadequate supports and programming for both the student and the teacher. The aim of this paper is to highlight the difficulties such students have and to suggest solutions to improve the quality of education provided for these students. Language: en
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".