Adolescent Dating Violence Prevention: Teaching Social Justice Oriented Skills and Strategies to Undergraduate-Level Teachers and Social Workers
Bibliographic record
Abstract
Youth from socially marginalized populations are at increased risk of experiencing adolescent dating violence (ADV), since they are often directly impacted by root causes of violence (e.g., homophobia, racism). Because structural inequalities impact youth’s experience of ADV, ADV is a social justice issue. In this paper, we describe a symposium series that taught education and social work students about their role in preventing ADV through a social justice lens. We present a pilot evaluation of the symposium series using survey ( n = 34) and interview ( n = 7) data. Results of this study (quantitative and qualitative) suggest students showed an increase in willingness and confidence to prevent and respond to ADV through a social justice lens after completing the symposium series. This work highlights the importance of incorporating critical theory into ADV prevention efforts, especially as it relates to serving youth who are marginalized and for promoting social justice in 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".