Taking action on violence through research, policy, and practice
Bibliographic record
Abstract
BACKGROUND: Violence is a critical public health problem associated with compromised health and social suffering that are preventable. The Centre for Global Health and Health Equity organized a forum in 2014 to identify: (1) priority issues related to violence affecting different population groups in Canada, and (2) strategies to take action on priority issues to reduce violence-related health inequities in Canada. In this paper, we present findings from the roundtable discussions held at the Forum, offer insights on the socio-political implications of these findings, and provide recommendations for action to reduce violence through research, policy and practice. METHODS: Over 60 academic researchers, health and social service agency staff, community advocates and graduate students attended the daylong Forum, which included presentations on structural violence, community violence, gender-based violence, and violence against marginalized groups. Detailed notes taken at the roundtables were analyzed by the first author using a thematic analysis technique. FINDINGS: The thematic analysis identified four thematic areas: 1) structural violence perpetuates interpersonal violence - the historical, social, political and economic marginalization that contributes to personal and community violence. 2) social norms of gender-based violence-the role of dominant social norms in perpetuating the practice of violence, especially towards women, children and older adults; 3) violence prevention and mitigation programs-the need for policy and programming to address violence at the individual/interpersonal, community, and societal levels; and 4) research gaps-the need for comprehensive research evidence made up of systematic reviews, community-based intervention and evaluation of implementation research to identify effective programming to address violence. CONCLUSIONS: The proceedings from the Global Health and Health Equity Forum underscored the importance of recognizing violence as a public health issue that requires immediate and meaningful communal and structural investment to break its historic cycles. Based on our thematic analysis and literature review, four recommendations are offered: (1) Support and adopt policies to prevent or reduce structural violence; (2) Adopt multi-pronged strategies to transform dominant social norms associated with violence; (3) Establish standards and ensure adequate funding for violence prevention programs and services; and (4) Fund higher level ecological research on violence prevention and mitigation.
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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 | 0.343 | 0.248 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.017 | 0.073 |
| Scholarly communication | 0.043 | 0.028 |
| Open science | 0.008 | 0.031 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".