Bibliographic record
Abstract
Community pharmacy practice is primary care. There, I said it. But many folks don’t agree. Community pharmacists are an important, but largely unrecognized, part of our primary health care system. Recently, I was working on a team grant that contained a few different projects, including a community pharmacy‒based smoking cessation study. The team members (policy-makers and researchers) kept talking about “the primary care project” (the one with family physicians) and the “pharmacy project.” I objected to the terminology, insisting that pharmacy is primary care, so why don’t we present a broader view of primary care (one that includes pharmacy). Eventually, they agreed, but it was enlightening that getting that point across to a bunch of “primary care” researchers was so difficult. Part of the problem is that it is so entrenched that primary care = family physicians, and we just accept that as fact. Indeed, most people equate primary care only with family physicians. Nothing against family physicians, but this ignores the much bigger picture of primary care. And, given that about a third of Canadians do not have or cannot easily see a family physician,1 this places more importance on the “other” parts of primary care.
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 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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.247 | 0.070 |
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".