Contexts and Dynamics of School Violence: A Multi-Method Investigation in an Ontario Urban Setting
Bibliographic record
Abstract
The issue of bullying, among school age children, has been popularized by North American news media. These media frame bullying as a violent epidemic plaguing our schools, resulting in school officials implementing new anti-violence intervention and prevention programs. However, popular media and school administrators often do not rely on research with consistent definitions for bullying behavior to inform these changes. As a result, the term bullying has become quite ubiquitous, conflating bullying behavior with other forms of youth violence. My research aims to delineate the contextual influences for youth violence and the types of violence youth engage in. I argue that sociology can contribute to the study of bullying by elaborating on the roles of three kinds of contexts: immediate networks, neighborhoods and micro-geographies, and status situations. Further, gender can also be a consistent conditioning influence on those contextual effects. This study utilizes a multi-method approach to better understand the contexts and dynamics of youth violence. My quantitative component uses data from systematic social observations of all Hamilton public school neighborhoods, Hamilton Safe School Surveys and the 2006 national census. These methods build on different contexts for youth violence. While the survey findings used in the quantitative portion of this thesis examine broad contextual influences, my qualitative interviews develop micro-geographic contexts for youth violence. Using these data sources, I found significant relationships between gender, age, physical disorder and types of violence used by students. My qualitative component used interviews conducted with fifteen Hamilton youth from a variety of different neighbourhood backgrounds to understand youth’s social dynamics in different kinds of violence. I found dynamics that were consistent with the types of in-school violence described by Randall Collins (2008, 2011) and different types for violence used by male and female students for similar social ends. It is my hope that these findings can be used to better inform violence intervention and prevention policies within Ontario schools.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 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".