Factors influencing the location of practice of residents and interns in British Columbia : implications for policy making
Bibliographic record
Abstract
Up to the middle of the 1970's most government policies dealing with physician manpower dealt with the problems of increasing the supply of physicians, rather than changing the geographic disparity of physicians between urban and rural areas. In 1983 the British Columbia government introduced legislation (passed in a modified form in 1985) that would restrict certain groups of physicians from obtaining Medical Service Plan billing numbers in certain areas of the province, in an attempt to change the geographic distribution of physicians in this province. Regulation is only one of a number of approaches to altering the distribution of physicians. The purpose of this study is to attempt to recommend other approaches that could be used to alter the geographic distribution of physicians, based on the factors which the residents and interns of British Columbia would consider necessary before they will establish practices in the rural areas of the province. The literature was examined to determine the present supply and distribution of physicians in the province of British Columbia. It was shown that the metropolitan areas had much higher concentrations of physicians than did the non-metropolitan regions. The literature was then searched to determine what types of policies had been used in an effort to change this geographic disparity and also to determine what factors influence physicians to locate their practices where they do. From this research a questionnaire was developed and mailed to all residents and interns registered in the University of British Columbia medical program in the academic year 1984-85. A response rate of 31.8% was obtained in this survey. It was found that many physicians were raised in large communities and planned to locate their practices in similar geographic areas to where they were raised. It was also found that the factors which the residents and interns considered to be the most important fell into the "Fixed Determinant" category, that is factors that are personal preferences of the physician. This makes it very difficult to formulate any type of non-regulatory policy to affect the geographic distribution of physicians in British Columbia
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".