Bibliographic record
Abstract
This thesis applies the econometric projection approach to forecast the numbers of general practitioners (GPs) in Saskatchewan for the next 15 years at both provincial and the Regional Health Authorities (RHAs) levels. The projection results will provide the estimated level of GPs up to 2021 for policy makers to adjust their decision on health professionals’ planning. Three hypothesized scenarios, which include the changes in population proportion, average income for GPs and a combination of both, are used for projections based on the regression results. The projections suggest a 4.34% expected annual increase of GPs if the proportions of children and seniors increase or decrease according to prediction for the next 15 years for Saskatchewan. At the RHAs level, 4.5% to 10.7% expected annual rate of increase for numbers of GPs is projected for the northern RHAs and Saskatoon RHA, while the expected increase for other urban RHAs will experience less than 1.5% increases. The predicted changes in average income for GPs show insignificant effect for the expected changes in numbers of GPs. However, the second and third scenarios are not extended to the RHAs level due to lack of information, which requires additional data for both Saskatchewan physicians and population for further projection analysis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".