Students with Learning Disabilities: The Application of Goffman's Stigma in the Inclusive Classroom
Bibliographic record
Abstract
This case study provides a qualitative glimpse into one inclusive classroom in Northern Ontario. It explores the nature of peer interactions of students with learning disabilities (LD) and uses Goffman's concept of stigma to analyze how students with LD react or act within the classroom. Twenty-five children were observed on a daily basis for seven weeks and participant observation was the primary method of data collection. Of these 25 children, 9 had a LD. This study found that sadness, aggression, and competence were recurring themes in student-peer interactions. This study reveals that the major themes presented reflect what studies have already posited on peer relationships and emotional functioning of students with LD; these studies, by and large, are American in nature, and thus this has major implications for future research within the Canadian context.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.027 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".