Engaging populations living with vulnerable conditions in community‐based research: A concept mapping approach to understanding positive practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The goal of this research is to identify positive practices used when conducting community‐based research with people living with vulnerable conditions. Community‐based research practitioners who participated in the research included 37 researchers, community partners, program planners, and government employees, working in health, human services, children and youth, and education sectors. Concept mapping, a participatory stakeholder‐driven process, was used to generate a framework of how community‐based research practitioners responded to the complex environments of people living with vulnerable conditions when conducting research. Respondents generated positive practices, determined relationships among practices, and rated practices on frequency of use and perceived effectiveness. This study revealed 7 clusters of positive practices: ethical practices, participant supports, social accountability, community involvement, language competence, financial compensation, and project management.
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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 | 0.039 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.010 |
| 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 it