Improving Health Care Globally: A Critical Review of the Necessity of Family Medicine Research and Recommendations to Build Research Capacity
Bibliographic record
Abstract
An invitational conference led by the World Organization of Family Doctors (Wonca) involving selected delegates from 34 countries was held in Kingston, Ontario, Canada, March 8 to 12, 2003. The conference theme was "Improving Health Globally: The Necessity of Family Medicine Research." Guiding conference discussions was the value that to improve health care worldwide, strong, evidence-based primary care is indispensable. Eight papers reviewed before the meeting formed the basic material from which the conference developed 9 recommendations. Wonca, as an international body of family medicine, was regarded as particularly suited to pursue these conference recommendations: 1. Research achievements in family medicine should be displayed to policy makers, health (insurance) authorities, and academic leaders in a systematic way. 2. In all countries, sentinel practice systems should be developed to provide surveillance reports on illness and diseases that have the greatest impact on the population's health and wellness in the community. 3. A clearinghouse should be organized to provide a central repository of knowledge about family medicine research expertise, training, and mentoring.4. National research institutes and university departments of family medicine with a research mission should be developed. 5. Practice-based research networks should be developed around the world.6. Family medicine research journals, conferences, and Web sites should be strengthened to disseminate research findings internationally, and their use coordinated. Improved representation of family medicine research journals in databases, such as Index Medicus, should be pursued.7. Funding of international collaborative research in family medicine should be facilitated.8. International ethical guidelines, with an international ethical review process, should be developed in particular for participatory (action) research, where researchers work in partnership with communities. 9. When implementing these recommendations, the specific needs and implications for developing countries should be addressed.The Wonca executive committee has reviewed these recommendations and the supporting rationale for each. They plan to follow the recommendations, but to do so will require the support and cooperation of many individuals, organizations, and national governments around the world.
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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 | 0.151 | 0.258 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.026 | 0.023 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".