Utilization of primary health care nurse practitioners in rural northern communities to alleviate the physician shortages and retention issues / by Susan Fairservice.
Bibliographic record
Abstract
The purpose of this research project is to critically examine primary health care services \nand analyze alternative solutions to the physician recruitment and retention issue in rural, \nnorthern, and remote communities in Ontario. Primary health care nurse practitioners, (PHCNPs) \nare a safe, cost-effective solution to alleviate this dilemma in these communities. \nThe needs assessment, conceptual framework and literature review demonstrated that \npopulations living in rural, northern and remote communities have decreased access to Health \nCare Providers, show that PHCNPs are a cost-effective and safe alternative to physicians, and \ndemonstrate that recruiting nurses from rural and remote communities to become PHCNPs is \nbeneficial to the communities. The Population Health Model validated that the health care needs \nof individuals in rural, northern and remote communities are not being met \nTo alleviate the physician shortage and retention issue in Ontario and particularly rural, \nnorthern and remote communities in Ontario the Ministry of Health and Long Term Care \n(MOHLTC) could: \nProvide funding to Registered Nurses in northern, rural and remote \ncommunities to become PHCNPs. \nIncrease the number of PHCNP run clinics. \nContinue to support and increase the number of Family Health Teams in \nOntario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".