Bullying Experiences Among First Nations Youth: Identifying Effects on Mental Health and Potential Protective Factors
Bibliographic record
Abstract
Bullying represents a substantial issue facing Canadian youth, and is associated with negative outcomes across domains of function throughout the lifespan. Despite significant literature examining bullying involvement among adolescents in Canada, a paucity of research explores the bullying experiences of First Nations, Metis and Inuit (FNMI) youth. This is particularly concerning, as these youth may be at higher risk for bullying and its related consequences due to the cultural marginalization and systemic inequalities experienced by Indigenous peoples nationwide. The present study aims to address this gap in the literature, examining the bullying experiences of FNMI youth, the effects of these experiences on mental health and well-being, and the potential moderating effect of three protective factors (cultural, school and peer connectedness), using longitudinal data collected from a cohort of FNMI adolescents in a large school district in southwestern Ontario. Findings indicated that FNMI youth in this sample experienced increased bullying victimization and perpetration as compared to national averages, and that greater cumulative bullying victimization was associated with more negative mental health. Further, despite no apparent moderating effect, all three of the identified protective factors predicted mental wellbeing independent of bullying victimization. Results support a tiered approach to intervention, confirming the merit of culturally relevant, school-based programming that incorporates these factors, as well as suggesting the need for targeted bullying interventions to promote resilience and well-being, and mitigate risk among FNMI youth experiencing bullying.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Primary study of bullying experiences and mental health among First Nations youth; the object is bullying, not research practice.
The study examines bullying and mental health among First Nations, Metis and Inuit youth, not research itself.
Social/developmental study of bullying among Indigenous youth, not the research system.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".