Institutional community engagement leader perspectives on supporting ethical community-engaged research
Bibliographic record
Abstract
Introduction: Over the last couple of decades, there has been a growing awareness of the value of community-engaged research (CEnR). Simultaneously, many academic institutions have established centralized support for CEnR. For example, dozens of academic medical centers in the United States receive National Institutes of Health (NIH)-funded Clinical and Translational Science Awards (CTSAs) and have embedded community engagement programs (CE) whose primary expertise and mission is to advance CEnR at their institutions. Methods: As part of a larger interview study aiming to learn more about how institutional CE programs and HRPPs work together, we analyzed interviews with CE program leaders at academic medical centers that receive funding from the NIH CTSA program to identify barriers and strategies to conducting CEnR at their institutions, primarily focusing on the relationships with Institutional Review Boards (IRBs). Results: We identified three categories in the interviews: barriers and strategies vis-à-vis IRBs to address 1) CE/IRB relationships; 2) Understanding issues; and 3) Structural and resource issues. Conclusions: CTSA CE program leaders have experience implementing solutions to common barriers to IRB review faced by CEnR researchers. The barriers they face in these three categories and the strategies they use to overcome them can provide helpful insights to others who hope to facilitate CEnR research at their institutions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
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 | 0.158 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.049 |
| Scholarly communication | 0.029 | 0.018 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.011 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".