Primary Care Research: Looking Back and Moving Forward With Reflections on NAPCRG’s First 50 Years
Bibliographic record
Abstract
NAPCRG celebrated 50 years of leadership and service at its 2022 meeting. A varied team of primary care investigators, clinicians, learners, patients, and community members reflected on the organization's past, present, and future. Started in 1972 by a small group of general practice researchers in the United States, Canada, and the United Kingdom, NAPCRG has evolved into an international, interprofessional, interdisciplinary, and intergenerational group devoted to improving health and health care through primary care research. NAPCRG provides a nurturing home to researchers and teams working in partnership with individuals, families, and communities. The organization builds upon enduring values to create partnerships, advance research methods, and nurture a community of contributors. NAPCRG has made foundational contributions, including identifying the need for primary care research to inform primary care practice, practice-based research networks, qualitative and mixed-methods research, community-based participatory research, patient safety, practice transformation, and partnerships with patients and communities. Landmark documents have helped define classification systems for primary care, responsible research with communities, the central role of primary care in health care systems, opportunities to revitalize generalist practice, and shared strategies to build the future of family medicine. The future of health and health care depends upon strengthening primary care and primary care research with stronger support, infrastructure, training, and workforce. New technologies offer opportunities to advance research, enhance care, and improve outcomes. Stronger partnerships can empower primary care research with patients and communities and increase commitments to diversity and quality care for all. NAPCRG offers a home for all partners in this work.
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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 | 0.146 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.023 | 0.054 |
| Scholarly communication | 0.037 | 0.037 |
| Open science | 0.007 | 0.023 |
| Research integrity | 0.044 | 0.080 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".