A review protocol on research partnerships: a Coordinated Multicenter Team approach
Bibliographic record
Abstract
BACKGROUND: Research partnership approaches, in which researchers and stakeholders work together collaboratively on a research project, are an important component of research, knowledge translation, and implementation. Despite their growing use, a comprehensive understanding of the principles, strategies, outcomes, and impacts of different types of research partnerships is lacking. Generating high-quality evidence in this area is challenging due to the breadth and diversity of relevant literature. We established a Coordinated Multicenter Team approach to identify and synthesize the partnership literature and better understand the evidence base. This review protocol outlines an innovative approach to locating, reviewing, and synthesizing the literature on research partnerships. METHODS: Five reviews pertaining to research partnerships are proposed. The Coordinated Multicenter Team developed a consensus-driven conceptual framework to guide the reviews. First, a review of reviews will comparatively describe and synthesize key domains (principles, strategies, outcomes, and impacts) for different research partnership approaches, within and beyond health (e.g., integrated knowledge translation, participatory action research). After identifying commonly used search terminology, three complementary scoping reviews will describe and synthesize these domains in the health research partnership literature. Finally, an umbrella review will amalgamate and reflect on the collective findings and identify research gaps and future directions. We will develop a collaborative review methodology, comprising search strategy efficiencies, terminology standardization, and the division of screening, extraction, and synthesis to optimize feasibility and literature capture. A series of synthesis and scoping manuscripts will emerge from this Coordinated Multicenter Team approach. DISCUSSION: Comprehensively describing and differentiating research partnership terminology and its domains will address well-documented gaps in the literature. These efforts will contribute to and improve the quality, conduct, and reporting of research partnership literature. The collaborative review methodology will help identify and establish common terms, leverage efficiencies (e.g., expertise, experience, search and protocol design, resources) and optimize research feasibility and quality. Our approach allows for enhanced scope and inclusivity of all research user groups and domains, thereby contributing uniquely to the literature. This multicenter, efficiency and quality-focused approach may serve to inspire researchers across the globe in addressing similar domain challenges, as exist in this rapidly expanding field.
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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 | 0.303 | 0.374 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.083 | 0.029 |
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".