Experiences of Governance in the Context of Community-Based Research: Structures, Problems and Theory
Bibliographic record
Abstract
Governance is a response to a recognition that traditional forms of decision-making have become inadequate to address complex societal and health problems generated by significant social and global changes (Chhotray & Stoker, 2009). The contributions of scientific and technical knowledge towards solving these complex problems have also been recognized as insufficient (Jasanoff, 2007). Community-based research (CBR) is an approach to research which is designed to make use of the knowledge of community and university members and their participation and collaboration ―in all phases of the research process, with a shared goal of producing knowledge that will be translated into action or positive change for the community‖ (Lantz, Israel, Schulz & Reyes, 2006, p. 239). However, although the contributions of lay knowledge have been acknowledged, how governance or collaborative decision-making is arranged in the context of community-based research is not well described in the literature. In order to address this knowledge gap, a study was undertaken in which in-depth interviews were conducted with community and university members of Canadian CBR collaborations to determine their governing experiences. Results are reported in a thesis by research papers. The first paper focuses on describing the governance structures that CBR collaborations used. In the second paper, the nature and content of problems which occurred in governing CBR collaborations, point to the importance of theory for conceptualizing and solving governance problems. To develop a theory of participation in governance of community-based research, the third paper uses Arnstein‘s theory of participation to propose a grounded theoretical basis for implementing participation in governance of CBR collaborations (Arnstein, 1969). Governance is a means of organizing, shaping and steering a course of decision-making. Governance is a critical component in the organization of knowledge production. Study and theory of governance in community-based research may help in improving understanding and implementation of a critical population health practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".