Capacity development among academic trainees in community-based primary health care research: The Aging, Community and Health Research Unit Experience
Bibliographic record
Abstract
Health care system capacity and sustainability to address the needs of an aging population are a challenge worldwide. An aging population has brought attention to the limitations associated with existing health systems, specifically the heavy emphasis on costly acute care and insufficient investments in comprehensive primary health care (PHC). Health system reform demands capacity building of academic trainees in PHC research to meet this challenge. The Aging, Community and Health Research Unit at McMaster University has purposefully employed a capacity building model for interdisciplinary trainee development. This paper will describe the processes and outcomes of the model, outlining how the provision of funding, mentorship, and a unique learning environment enables capacity building in networking, collaboration, leadership development, and knowledge mobilization among its trainees. The reciprocal advancement of the research unit through the knowledge and productivity of trainees will also be detailed.
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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 | 0.047 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".