Community Consultations to Support Scoping Review Knowledge Dissemination
Bibliographic record
Abstract
Scoping reviews are a valuable form of literature review used to synthesize many types of evidence found in academic literature. Amidst the recommended best practices for conducting scoping reviews, little attention has been given to how to conduct community consultations as part of scoping review processes. The objective of this article is to describe one form that community consultation can take. As the final step in a scoping review project examining the stigmatization and discrimination of persons experiencing homelessness, our research team conducted a community consultation, designed as a Knowledge Café workshop, with 25 participants who had lived experiences of homelessness (past and present) or were service providers in the homelessness sector. The 3-hour workshop was conducted in a central public library with participants seated at different roundtables. The workshop was divided into four discussion periods during which participants described experiences, outcomes, or interventions related to the stigmatization and discrimination of persons experiencing homelessness. At the end of the workshop, participants completed a brief survey about the quality of the workshop, aspects that worked well, and what could be improved. Participants reported appreciating that the workshop provided a forum for combining research findings with personal stories, as well as opportunities to make or revive professional connections. Participants also reported that tangible event outcomes, a more future-oriented focus on solutions, and a longer event would have improved their experience. Study findings contribute to the literature on how to engage with community around collaborative problem-solving and the importance of incorporating diverse perspectives, fostering empathy and inclusivity, and translating ideas into actionable steps.
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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 | 0.452 | 0.710 |
| Meta-epidemiology (narrow) | 0.005 | 0.008 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.056 | 0.039 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.011 | 0.046 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.180 | 0.069 |
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".