Regular doctor, changing doctor, no doctor: does it make a difference to rural residents?
Bibliographic record
Abstract
INTRODUCTION: In Canada, a larger proportion of rural residents than urban residents do not have a regular physician. In addition to lacking physicians, many rural communities also have a high rate of physician turnover. In order to discover the effect of this we compared health status, lifestyles, preventative care, and perceptions of the health system among rural residents with a regular doctor, those who did not have a regular doctor, and those whose regular doctor changed. METHODS: We examined data from the 1995 Newfoundland Panel on Health and Medical Care and the 2001 Adult Health Survey. In each year, we compared these three groups of residents using chi2 tests and multiple logistic regression. RESULTS: In 1995, 78.1% of rural residents had a regular doctor, 8.4% had changing doctors, and 13.5% did not have a regular doctor. In 2001, 84.6% of rural residents had a regular doctor, 4.9% had changing doctors, and 10.6% did not have a regular doctor. In 1995, compared with those with regular doctors, those whose doctors changed were less likely to have a disability or physical restriction, have their blood pressure checked or be satisfied with the healthcare system; while those without a regular physician were less likely to have poor health status, preventative care or be satisfied with the healthcare system. In 2001, there were no differences between those with a regular doctor and those whose doctor changed. Compared with those with a regular doctor, those without a regular doctor were less likely to have poor health status. CONCLUSION: The proportion of rural residents who had a regular doctor increased between 1995 and 2001. Disparities between those who had a regular doctor and those with a frequently changing doctor diminished.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".