Bibliographic record
Abstract
Weapon carrying at school has been explained by a number of theories, but two dominate the literature: being fearful and trying to protect oneself from harm (fear-victimization hypothesis) or displaying behaviour consistent with a deviant lifestyle (lifestyle theory). This study replicated previous research by investigating the relative and combined influence of individual level processes related to weapon carrying, as hypothesized by the fear-victimization hypothesis (i.e., fear of victimization and victimization experiences) and lifestyle theory (i.e., alcohol and drug use). This study extended previous research by also considering an ecological model of weapon carrying by examining school level processes that may impact student weapon-carrying. Data was obtained from students (N= 50,334) in grades 8-12 in 69 schools in Western Canada who completed the Safe Schools and Social Responsibility Survey. Multilevel modeling was used to evaluate both individual and school level variables that underlie the two major theories of weapon carrying among youth. Results at the individual level provided support for both the fear-victimization hypothesis and the lifestyle theory, suggesting multiple pathways to deviant behaviour. Support was also found for the hypothesis that some school-level variables, as reflected in the collective experiences of the student body, influenced the relationship between individual level processes (i.e., a students reported fear of victimization, victimization experiences, and substance use) and weapon carrying.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".