An innovative approach to addressing gender-based violence and adverse childhood experiences: An evaluation of the Alliance against Violence and Adversity (AVA) community agency internship program
Bibliographic record
Abstract
Gender-based violence (GBV) and Adverse Childhood Experiences (ACEs) are associated with numerous detrimental health, social and economic impacts across the life course. Despite overwhelming evidence of GBV and ACEs as global health concerns, current approaches to prevent and respond to GBV and ACEs have been insufficient to address these problems. Drawing on evaluation and implementation research, innovations in GBV and ACEs training may help solve this problem. This study evaluated the Community Agency Internship Program (CAIP) of the Alliance against Violence and Adversity (AVA), a health research training platform that funds graduate student interns in community agencies focused on GBV and ACEs interventions in Canada. This evaluation focused on interns’ and community agency leaders’ self-reported perspectives of: the interns’ tasks and activities conducted during the internship, barriers and challenges, benefits and impacts, and satisfaction with CAIP. A pilot evaluation employed survey data collected between 2022 and 2024. Nine interns and four community agency leaders completed surveys at the conclusion of the CAIP placement. Quantitative and qualitative data were analyzed using descriptive statistics and deductive thematic analysis, respectively. The CAIP positively impacted interns’ and leaders’ professional practice, goals, and personal growth, with most reporting high satisfaction with the program. Interns became comfortable with the pace of community-based work and engaging with diverse community members. Community agency leaders reported readiness to integrate research within their organizations and emphasized how the CAIP provided them with resources to engage in research and evaluation of their practice and implementation of services. The AVA CAIP promoted community agencies’ engagement in evaluation activities, and increased reciprocal learning about uptake, dosage, and maintenance of innovative programs to optimize service delivery to address the crisis of GBV and ACEs in Canada. • It is well documented that Gender-based violence (GBV) and adverse childhood experiences (ACEs) have profound health, social, and economic effects throughout the lifespan, yet current prevention and response strategies remain insufficient. • The Alliance Against Violence and Adversity (AVA) Community Agency Internship Program (CAIP) is an innovative training initiative that connects graduate student interns with community agencies to tackle GBV and ACEs through integrated research and practice. • Evaluation of AVA’s CAIP shows that the program enhances interns' and community leaders' professional growth, personal development, and aspirations while preparing agencies to integrate research and evaluation into their practices. • AVA’s CAIP equips community agencies to adapt implementation and evaluation strategies, optimize evidence-based service delivery, and bridge the gap between research and practice in addressing GBV and ACEs in Canada. • As a reproducible model, the AVA CAIP illustrates how reciprocal learning, collaborative research, and community-driven approaches can effectively address GBV and ACEs while advancing the field through program evaluation and implementation science.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".