Towards building consensus: Revisiting key principles of CBPR within the First Nations/Aboriginal context
Bibliographic record
Abstract
Community based participatory research as a preferred approach to research with First Nations and Aboriginal communities has contributed to new terminologies, new methodologies, and new directions in research relationships. One of the ongoing challenges is to articulate and operationalize the principles for CBPR with these communities. This paper reflects on the nine principles articulated by LaVeaux and Christopher in the context of a long term community-academic research partnership at Standing Buffalo First Nations, Saskatchewan, Canada. Within this application, we begin to critique the various principles and to reframe these principles to increase their utility in informing community based research in the First Nations/Aboriginal context.
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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 | 0.524 | 0.330 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.030 | 0.205 |
| Scholarly communication | 0.040 | 0.039 |
| Open science | 0.018 | 0.036 |
| Research integrity | 0.019 | 0.031 |
| Insufficient payload (model declined to judge) | 0.003 | 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".