Geographic Accessibility of Community Pharmacies in Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Proximity is an important component of access to healthcare services. Recent changes in generic pricing in Ontario have caused speculation about pharmacy closures. However, there is little information on the current geographic accessibility of pharmacies. Therefore, we studied geographic access to pharmacies and modelled the impact of possible closures. METHODS: We used location data on the 3,352 accredited community pharmacies from the Ontario College of Pharmacists and population estimates at the census dissemination block level. Using network analysis, we determined the share of Ontario's population who reside in a census dissemination block within three road travel distances of a community pharmacy: 800 m (walking), 2 km and 5 km (driving). We then simulated the effects on these measures of 10% to 50% reductions in the number of community pharmacies in Ontario. RESULTS: Approximately 63.6% of the Ontario population reside in a dissemination block located within walking distance of one or more pharmacies; 84.6% and 90.7% reside within 2-km and 5-km driving distances, respectively. Randomly removing 30% of Ontario's community pharmacies reduces these estimates to 56.0%, 81.4% and 89.0% for each distance, respectively; a 50% reduction results in 48.3%, 77.1% and 87.2%, respectively. CONCLUSIONS: Pharmacies are geographically accessible for a majority of the Ontario population. Moreover, it appears that modest closures would have only a small impact on geographic access to pharmacies. However, closures may have other impacts on access, such as cost, waiting time and reduced patient choice.
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.
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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it