Bibliographic record
Abstract
Rural health services are an essential part of the fabric of rural life. Despite the fact that about 19%1 of Canadians live in rural areas, only 8%2 of physicians practise in rural areas. The figure for family physicians is 14% compared to 2% of specialists.2 This means that rural physicians and rural health teams will deal with higher workloads and more complex patients, all within the context of limited resources and further distances from tertiary care. Lack of a national workforce plan, lack of a service plan for communities/hospitals and a lack of a culture of societal responsibility from training and licensing institutions have led us to this problem. The SRPC is a small organisation which hopes to inspire big changes in our current system. We had incredible success with our National Advanced Skills Training Programme and your executive and chief operating officer are working hard to find continued funding for this valuable programme. We are hard at work defining a rural health and human resource strategy to inform policymakers and educational institutions to make socially accountable decisions when it comes to training our future colleagues. We are actively working on creating what we see as the core values of rural medical education to help future practitioners see the joy in comprehensive generalist practice. As members, you can help with this work. Please consider attending our 32nd Annual Rural and Remote Medicine Conference April 24–26/2025. This year’s conference theme, ‘Where the Rivers Meet: Building Bridges in Rural Medicine for a Brighter Future’, is inspired by the convergence of rivers in Winnipeg, our host city. The theme symbolises the power of connection – bringing together rural healthcare professionals to share knowledge, foster community and address the challenges of burnout that have become even more pressing post-pandemic. There will be opportunities to learn and contribute to the aforementioned topics with colleagues and thought leaders. As a volunteer organisation, we will always find a place for keen and passionate colleagues who want to advance the mission of the society. I thank you again for the work you do to support your communities. It is time for decision-makers to know that the people who grow our food, tend to our resources and protect our landscapes deserve equitable access to healthcare. Living in these places is not simply a choice, but also a privilege.
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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.005 | 0.025 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.069 | 0.030 |
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".