DOI: 10.1177/0143034310377150 Racial Bullying and Victimization in Canadian
Bibliographic record
Abstract
abstract Numerous individual factors, including race, have been identified to date that may place children at risk for bullying involvement. the importance of the school’s environment on bully-ing behaviours has also been highlighted, as the majority of bullying occurs at school. the variables associated with racial bullying and victimization, however, have rarely been specifically examined. the purpose of the current study, therefore, was to determine which individual- and school-level factors are associated with racial bully-ing and victimization. Canadian records from the 2001/2002 health Behaviors in School-Aged Children Survey (hBSC) were used for the current analyses. Participants included 3,684 students and their prin-cipals from 116 schools from across the country. Results indicated that racial bullying and racial victimization were more strongly related to individual factors such as race and sex than school-level factors. African-Canadian students were found to engage in racial bullying as well as report being racially victimized. In addition, school climate did not account for observed differences between schools on racial bullying and victimization, but racial bullying appeared to decrease in support-ive schools with higher teacher diversity. key words: children; racial bullying; racial minority groups; school; victimization Bullying is a serious relationship problem in which children use power through frequent acts of aggression to intimidate and control others, and make others feel powerless in their relationships (Pepler et al., 1999), and has been identified as a significant problem in many dif-
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.439 | 0.051 |
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".