Can we Build on Social Movement Theories to Develop and Improve Community‐Based Participatory Research? A Framework Synthesis Review
Bibliographic record
Abstract
A long-standing challenge in community-based participatory research (CBPR) has been to anchor practice and evaluation in a relevant and comprehensive theoretical framework of community change. This study describes the development of a multidimensional conceptual framework that builds on social movement theories to identify key components of CBPR processes. Framework synthesis was used as a general literature search and analysis strategy. An initial conceptual framework was developed from the theoretical literature on social movement. A literature search performed to identify illustrative CBPR projects yielded 635 potentially relevant documents, from which eight projects (corresponding to 58 publications) were retained after record and full-text screening. Framework synthesis was used to code and organize data from these projects, ultimately providing a refined framework. The final conceptual framework maps key concepts of CBPR mobilization processes, such as the pivotal role of the partnership; resources and opportunities as necessary components feeding the partnership's development; the importance of framing processes; and a tight alignment between the cause (partnership's goal), the collective action strategy, and the system changes targeted. The revised framework provides a context-specific model to generate a new, innovative understanding of CBPR mobilization processes, drawing on existing theoretical foundations.
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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 | 0.065 | 0.092 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.023 | 0.016 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".