Knowledge Transfer and Exchange Processes for Environmental Health Issues in Canadian Aboriginal Communities
Bibliographic record
Abstract
Within Canadian Aboriginal communities, the process for utilizing environmental health research evidence in the development of policies and programs is not well understood. This fundamental qualitative descriptive study explored the perceptions of 28 environmental health researchers, senior external decision-makers and decision-makers working within Aboriginal communities about factors influencing knowledge transfer and exchange, beliefs about research evidence and Traditional Knowledge and the preferred communication channels for disseminating and receiving evidence. The results indicate that collaborative relationships between researchers and decision-makers, initiated early and maintained throughout a research project, promote both the efficient conduct of a study and increase the likelihood of knowledge transfer and exchange. Participants identified that empirical research findings and Traditional Knowledge are different and distinct types of evidence that should be equally valued and used where possible to provide a holistic understanding of environmental issues and support decisions in Aboriginal communities. To facilitate the dissemination of research findings within Aboriginal communities, participants described the elements required for successfully crafting key messages, locating and using credible messengers to deliver the messages, strategies for using cultural brokers and identifying the communication channels commonly used to disseminate and receive this type of information.
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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 | 0.023 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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; 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".