BULLYING IN A MULTICULTURAL CONTEXT The Influences of Race, Immigrant Status, and School Climate on the Incidence of Bullying in Canadian Children and Adolescents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it