Building Critical Community Engagement through Scholarship: Three Case Studies
Bibliographic record
Abstract
The Collaborative RESearch Team to study psychosocial factors in bipolar disorder (CREST.BD) is a multidisciplinary network dedicated to advancing science and practice around psychosocial issues associated with bipolar disorder (BD), improving the care and wellness of people living with bipolar disorder, and strengthening services and supports for these individuals. CREST.BD specializes in community-based participatory research, in which research is conducted as a partnership between researchers and community members. This article describes the evolution of the CREST.BD network and CREST.BD’s commitment to community-based participatory research in bipolar disorder research. Examples of CREST.BD projects using community-based participatory research to study stigma, quality of life, psychosocial interventions, and creativity in bipolar disorder are highlighted, and opportunities and challenges of engaging in community-based participatory research in bipolar disorder specifically and the mental health field more broadly are discussed. This article demonstrates how CBPR can be used to enhance the relevance of research practices and products through community engagement, and how community-based participatory research can enrich knowledge exchange and mobilization.Â
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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 | 0.041 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.047 | 0.022 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.008 | 0.032 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".