Knowledge Mobilization Strategies for Intimate Partner Violence Research in Canada: A Mixed Methods Study
Bibliographic record
Abstract
Knowledge mobilization (KMb) is the process of sharing research evidence to address important health and social issues, including intimate partner violence (IPV). While Canadian researchers contribute significantly to IPV research, their efforts to mobilize this knowledge beyond academic audiences are less known. This study used a mixed methods approach, integrating both quantitative and qualitative analyses to explore the KMb of Canadian IPV researchers to practice, policy, and public audiences. A systematic search identified 58 publicly available KMb products (e.g., news articles, infographics, reports, etc.). KMb products were analyzed inductively using qualitative content analysis and descriptive statistics. Most products focused on IPV interventions and understanding the problem of IPV. Common dissemination strategies across products were institutional/organizational websites and news websites. This study contributes to an emerging literature on how specific knowledge-sharing strategies can be used to promote the uptake of evidence, in this case, specific to IPV. Further research is needed to assess the effectiveness of these efforts to enhance policy and practice.
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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 | 0.034 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.022 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".