Pieces of the puzzle: Forming the picture of the future of family medicine
Bibliographic record
Abstract
The Canadian public continues to consider family doctors one of the most trusted and highly valued parts of our health care system. Starfield, Shi, and others have shown that access to family physicians, more than any other health professionals, results in better population health outcomes. Across Canada, family doctors are starting to receive more recognition, including better remuneration, for their services. In 2006, family medicine residency was the first choice of 31% of Canadian medical school graduates, compared with 24% just 3 years ago. These are good signs, but they are only a start. In general, the contribution of family physicians—as practitioners, teachers, researchers, and health system consultants—is still undervalued. Reversing family doctor shortages and stimulating more interest in careers as family physicians among medical students remain serious challenges. At the moment, imagining what the future holds for family medicine in Canada is like looking at a puzzle with several key pieces missing. Fortunately, many of the pieces (see below) are now on the table waiting to be placed in the puzzle to help complete the picture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.019 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".