Bibliographic record
Abstract
BACKGROUND: Pharmacists in Canada are assuming an increasingly important role in the provision of primary care services. This raises questions about access to pharmacy services among those with medical care needs. While there is evidence on proximity of residents of Ontario and Nova Scotia to community pharmacies, there is little evidence for the rest of Canada. I thus measured the availability of pharmacist services, both the number of community pharmacies and their hours of operation, at both the provincial and sub-provincial level in Canada. Next, I measured associations of indicators of medical need and the availability of pharmacist services across sub-provincial units. METHODS: I collected data, for each Forward Sortation Area (FSA), on medical need, measured using the fraction of residents aged 65 + and median household income, and pharmacist service availability (the number of community pharmacies and their hours of operation, divided by the FSA population). Linear regression methods were used to assess associations of FSA-level service availability and medical need. RESULTS: There are between 2.0 and 3.3 community pharmacies per 10,000 population, depending on the province. There are also provincial variations in the number of hours that pharmacies are open. Quebec pharmacies were open a median of 75 h a week. In Manitoba, pharmacies were open a median of 53 h a week. The per capita number of pharmacies and their total hours of operation at the FSA level tend to be higher in less affluent regions and in which the share of residents is aged 65 or older. Provincial differences in pharmacy availability were still evident after controlling for medical need. CONCLUSION: Community pharmacies in Canada tend to locate where indicators of health needs are greatest. The impact on patient health outcomes of these pharmacy locational patterns remains an area for future research.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".