Centering Reciprocity and Accountability in Community-Based Research: How Meaningful Relationships with a Community Advisory Group Impacted Survey Development
Bibliographic record
Abstract
Community advisory boards (CAB) or groups (CAG) are frequently included in qualitative community-based research (CBR), particularly in the early phases of assessing need, impact, and design of a research project. Projects with emancipatory, liberatory, or decolonial emphases include CAGs in the spirit of inclusivity, representation, transformation, truth-telling, and participation, but the methodological value and impact of such groups often remains under-explored in reports about the research. It is also relatively uncommon to use CAGs in quantitative research. In our survey research about post-secondary instructors’ experiences of receiving student disclosures of gender-based violence, we used a time-limited, task-specific CAG to assist with survey development. In this report from the field, we discuss our approach to the inclusion of a CAG in our research, which emphasized reciprocity and accountability to community, and we explore how the use of a CAG directly impacted and strengthened the quantitative study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.405 | 0.493 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.019 | 0.021 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".