Rural pharmacy in Canada: pharmacist training, workforce capacity and research partnerships
Bibliographic record
Abstract
OBJECTIVES: To characterize rural health care and pharmacy recruitment and retention issues explored in Canadian pharmacy strategic guidelines and Canadian Faculties of Pharmacy curricula; compare the availability of pharmacy workforce across Canadian jurisdictions; and identify models for potential collaborations between universities and rural pharmacies in the North. METHODS: Review of Canadian pharmacy strategic documents, Canadian Faculty of Pharmacy websites, Canadian pharmacy workforce data and relevant literature based on the search terms to identify university-rural community pharmacy initiatives. RESULTS: Three recent Canadian pharmacy strategic documents do not directly address issues related to rural and northern pharmacy practice, with recruitment and retention mentioned only in Canadian Pharmacists Association documents. Few Canadian Faculties of Pharmacy provide curricula on rural and northern health care issues or discuss rural recruitment and retention during training, with barriers to experiential rural practicums impeding placements. An innovative new partnership between the University of Waterloo School of Pharmacy and Gateway Rural Health Research Institute has the potential to enhance rural education, pharmacy services and community-based research. The number of pharmacists per 100,000 population in northern regions of British Columbia and the territories is low when compared with other Canadian provinces. In Australia, a model of university-rural pharmacy collaboration has been developed that may have the potential to inform future Canadian initiatives. CONCLUSIONS: Development of a coordinated, multifaceted approach involving universities, pharmacy professional associations and community-based research organizations in rural and northern regions of the country has the potential to enhance pharmacist education, practice recruitment, practice retention and community-based health outcomes research.
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 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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".