<i>Rural</i>360: incubating socially accountable research in the Canadian North
Bibliographic record
Abstract
People in Northern Newfoundland and Coastal Labrador (NNCL), Canada, face major challenges obtaining accessible and contextually-relevant healthcare. Rural360 is a socially accountable research incubator that provides funding for NNCL physicians to research solutions to these issues. NNCL graduates of the adjoined 6for6 research training program for rural physicians are invited to submit the research project they have conceptualised as part of that initiative as a letter of intent, and subsequently as a research proposal, to Rural360. These submissions are reviewed by relevant subject matter experts as part of the Rural360 adjudication process. This process is iterative and strives to guide and assist participants in refining their submission. The overarching objective of Rural360 is to collaborate with rural physicians to conduct, disseminate or otherwise catalyze unsupported community-based research in NNCL. In so doing, it is highly socially accountable, empowering participants to become change-makers who investigate contextually important health issues that emerge from NNCL communities.
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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 | 0.026 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.071 | 0.031 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".