Bibliographic record
Abstract
Reflecting on the process of sexual assault/ domestic violence protocol evaluation research This article discusses and reflects on the community engagement that brought together our complex partnership to conceptualise, design, conduct and communicate evaluation research on one community’s sexual assault and domestic violence (SADV) Protocol. Our article sits within the scholarship on community-university (CU) partnerships as a subcategory of the scholarship of engagement literature (see McNall et al. 2009). It looks at our partnership through the lens of Sadler et al.’s (2012) guidelines for ethical conduct of community-engaged research (CEnR) projects. We critically reflect on the extent to which our CU partnership practices and community-engaged research fit with the following guidelines: 1) Create an ethical framework; 2) Promote diversity; 3) Share decision-making; 4) Share benefits; 5) Train research partners. Our goal is to offer other community-engaged/ community-based participatory researchers (CBPR), protocol evaluation researchers, practice/service researchers, practitioners and service providers practical insights into community-engaged evaluation research while satisfying the principles of ethical conduct for community-engaged research. The context for this CEnR project starts with the work of the community partner. The Guelph-Wellington Action Committee on Sexual Assault and Domestic Violence (the Action Committee) is chaired by a local violence against women agency and represents 29 organisations from various sectors (including law enforcement, victim services, child welfare, social services, religious community, addictions and mental health, health care and education) within the Guelph-Wellington community which provide services and support to women and children who have experienced sexual assault and/or domestic violence. The Action Committee has been meeting in different forms for approximately 20 years. It is one of about 48 Domestic Violence Community Coordinating
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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 | 0.099 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.172 | 0.048 |
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".