BULLYING IN A MULTICULTURAL CONTEXT The Influences of Race, Immigrant Status, and School Climate on the Incidence of Bullying in Canadian Children and Adolescents
Bibliographic record
Abstract
Strong group affiliations based on race have been found in children at a very young age (Aboud, 1988) and may lead to a higher risk of involvement in bullying for certain racial groups. Little research, however, has addressed the relationship among bullying, race, and immigrant status in a Canadian sample. As well, few studies have directly examined racial bullying and victimization. Thus, the two studies in the current project aim to examine race and immigrant status as individual risk factors for bullying involvement, while also examining the individual- and school-level factors associated with racial bullying. In Chapter Two, an empirical examination of the relationship among race, immigrant status, and bullying and victimization in adolescence reveals that racial minority adolescents experience racial bullying. Immigrant status, however, does not appear to predict victimization, but it may be a risk factor for bullying others. In Chapter Three, a multilevel investigation of racial bullying and victimization at the individual and school levels indicates that African-Canadian students are at risk of engaging in both racial bullying and victimization, and that being male is also associated with participation
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".