Relations between bullying and distress among youth living in First Nations communities: Assessing direct and moderating effects of culture-related variables
Bibliographic record
Abstract
The well-being of Indigenous peoples continues to be affected by intergenerational effects of numerous harmful government policies, which are considered root causes for bullying and cyberbullying that exist in some communities. Despite ongoing stressors, Indigenous youth demonstrate resilience, which often appears grounded in connecting to their cultural identities and traditional practices. However, few studies have tested the direct and stress-buffering role of various aspects of culture in relation to well-being among First Nations youth. Analyses of the 2015–16 First Nations Regional Health Survey (RHS) revealed that bullying and cyberbullying were associated with increased psychological distress among youth aged 12–17 living in First Nations communities across Canada ( N = 4,968; weighted = 47,918), and that these links were stronger for females. Feelings of community belonging were directly associated with lower distress and buffered the relationships between bullying/cyberbullying and distress. Among youth who experienced cyberbullying, those who participated in community cultural events at least sometimes reported lower distress compared to those who rarely or never participated. Those who disagreed that traditional cultural events were important reported the highest levels of distress, but perceived importance of such events failed to buffer the associations between bullying/cyberbullying and distress. These national data highlight the importance of certain culture-related variables as key factors associated with the well-being of youth living in First Nations communities across Canada.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".