A Snapshot of Community Engagement in Research in the Context of an Evolving Public Health Paradigm: Review
Bibliographic record
Abstract
BACKGROUND: Community engagement is a work in process. Researchers continue to refine the process of collaboration and look to best practice and lessons learned for guidance in this relatively new model. OBJECTIVE: The aim of this study was to provide a snapshot of whether community engagement has been included in the design and implementation of research initiatives in Australia, Canada and the United Kingdom. The secondary aim is to identify the underlying themes present, to identify theories and tools that drive research. METHODS: A literature search was performed to identify studies that have been conducted to reduce the weight of the general population. RESULTS: The results of the study, which focused on the field of weight loss, indicate that scientific and technological advancements are the primary drivers of research. However, these new research initiatives have largely been undertaken in the absence of community engagement. CONCLUSIONS: The study concludes that initiatives need to adapt to a wider range of stakeholders, develop equitable community engagement platforms and take into consideration.
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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 | 0.029 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".