A snapshot of community-based research in Canada: Who? What? Why? How?
Bibliographic record
Abstract
Community-Based Research (CBR) is rapidly gaining recognitions as an important tool in addressing complex environmental, health and social problems. However, little is known about the Canadian CBR context. A web-based survey including 25 questions was circulated on list-servs and via targeted e-mails to investigate the status of CBR in Canada. Univariate and bivariate statistical analyses were performed to examine variables and relationships of interest. Our sample included a cross-section of CBR community and academic practitioners (n = 308). Respondents reported a wide range of project foci, experience, operating budgets and reasons for engaging in their last CBR endeavor. Academic partners were perceived to be most involved at all stages of the research process except dissemination. Service providers were also perceived as being very involved in most stages of research. Community members were substantially less engaged. High levels of satisfaction were reported for both CBR processes and outcomes. Respondents reported a number of positive outcomes as a result of their research endeavors, including changes in both agency and government policies and programs. Our study shows that CBR practitioners are engaged in research on a wide array of Canadian health and social issues that is making a difference. Finding appropriate levels of participation for community members in CBR remains an ongoing challenge.
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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 | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".