“I don’t think I get bullied because I am different or because I have autism”: Bullying Experiences Among Middle Years Children with Disabilities and Other Differences
Bibliographic record
Abstract
This study explores conceptualizations and experiences of bullying and victimization from the perspectives of 6 Canadian children (ages 10-13) with intersecting differences of race, ethnicity, language, and disability. Utilizing narrative and critical discourse analysis designs, alongside multi-method data collection approaches with creative participatory techniques, participants shared bullying experiences and theirre influence on school belonging. Participants highlighted (a) characteristics of bullies; (b) physical, verbal, social/relational aggressive experiences; (c) various strategies for managing bullying occurrences; and (d) notions of difference and victimization. This paper speaks to the importance of listening to the voices of children from traditionally oppressed groups, particularly those with autism and other disabilities, as their insights expand traditional understandings of categories of normalcy and difference within school spaces.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".