Educator Evaluation of Academic and Social Competence in Students with Acquired Brain Injury (ABI) Relative to Assessed Performance and Sense of Belonging
Bibliographic record
Abstract
Acquired brain injury (ABI) is the leading cause of death and disability amongst children \nand adolescents andpresents itself with challenges associated in cognitive, social, \nemotional, and behavioural domains. These changes may interfere with academic \nperformance and social inclusion, influencing self-esteem and personal success. The \ncurrent study examined a subset of data to capture the sense of academic and social \nbelonging for students with ABI as a function of the classroom teachers’ subjective \nperception of ability, their ABI knowledge, and student identification. Overall, a \ndiscrepancy was found between educators’ subjective ratings of student performance and \nstudents’ neurocognitive capacity. Educator knowledge and identification of ABI \ninfluenced student success in academic and social domains independent of teaching \napproach. This research has implications for the identification of ABI in the classroom \nand related challenges students experience. Educators are underprepared for the \nreintegration of students returning to school and lack appropriate knowledge and \nstrategies to accommodate individual needs.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".