Role of pharmacy education and pharmacy practice in developing pharmacists as researchers
Bibliographic record
Abstract
The International Pharmaceutical Federation (FIP) theme for World Pharmacist Day (25 Sep 2024) was ‘Pharmacists Meeting Global Health Needs’ [1]. This theme is reflective of the multitude of diverse roles pharmacists fulfill around the globe. These include independent pharmacist prescribing, participating in the development of new medications; pharmacovigilance activities such as antimicrobial stewardship to combat antibiotic resistance, a major global threat; contributing to health policy research to advocate for policies that improve access to medications and healthcare services; research and public health initiatives such as vaccination programs and health education campaigns to improve health outcomes in underserved populations; examining how telepharmacy and digital health can be expanded to provide pharmaceutical care in remote and underserved areas; studying the impact of climate change on health outcomes and the impact of medication use on climate change; and understanding occupational stress and burnout in pharmacists and the impact on the profession. Research is a core element that enables pharmacists to achieve these goals and be recognized for their important work. Moving forward, enhanced research activities can significantly advance pharmacy practice by advancing knowledge of how pharmacists best meet global health needs. Participating in international research collaborations enables pharmacists to share knowledge and best practices, contributing to a global effort to address health challenges [1].
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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 | 0.158 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.005 | 0.042 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".