Supporting the Use of Research Evidence by Community-Based Organizations in the Health Sector
Bibliographic record
Abstract
Community-based organizations are important stakeholders in health systems and research evidence can inform many aspects of their work, including their delivery of programs and services and their advocacy for broader system level supports. Unfortunately, there have been few visible efforts, such as those developed for other stakeholders (e.g., health system professionals and policymakers) to support the use of research evidence in community-based organizations. I have begun to address this need in this thesis through four manuscripts that collectively use a mix of approaches and methods to contribute to better supporting the use of research evidence by community-based organizations as well as to evaluating these efforts. Specifically, in the chapters I present: 1) a framework for supporting the use of research evidence by community-based organizations; 2) a scoping review of the key characteristics of community-based organizations; 3) a qualitative study of executive directors and program managers of community-based organizations in three sectors in Ontario, Canada (HIV/AIDS, diabetes, and mental health and addictions) to develop approaches to user-friendly summaries and peer-relevance assessments of systematic reviews; and 4) a protocol for a randomized controlled trial evaluating the effects of an evidence service on community-based AIDS service organizations' use of research evidence. Each of the chapters contributes to the development of a novel area of research in knowledge transfer and exchange and the thesis as a whole provides a framework, resources, and practical tools for those interested in supporting the use of research evidence by community-based organizations. A number of important areas for future research have emerged from this thesis including conducting long-term evaluations of efforts to support the use of research by community-based organizations, developing and refining theories related to whether, how and why they use research evidence, and developing additional strategies to support their use of research evidence, including deliberative dialogues and capacity building.
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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 | 0.693 | 0.782 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.023 | 0.022 |
| Science and technology studies | 0.014 | 0.028 |
| Scholarly communication | 0.054 | 0.040 |
| Open science | 0.010 | 0.031 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 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".