The International Pharmacists-as-Immunizers Partnership (IPIP)—Advancing Research on Pharmacist-Administered Immunizations Worldwide
Bibliographic record
Abstract
This article describes the formation of the International Pharmacists-as-Immunizers Partnership (IPIP), an international network of pharmacy practice researchers with an interest in pharmacist-administered immunizations. Using funds obtained from a university-sponsored grant, a two-day meeting was held at the University of Waterloo in Canada to discuss published and in-progress research on the topic, identify gaps and priorities for future research, and share implementation strategies used in different jurisdictions. Twelve researchers from five countries attended this initial meeting, identified from both personal networks and from authorship lists from published research. Small- and large-group discussions addressed a number of themes, including: clinical, economic and educational outcomes of the service; the perspectives of pharmacists, patients, and other health professionals; operational and policy factors influencing uptake; safety; and the immunizing pharmacist's role in disaster preparedness. Feedback on our first meeting and outcomes achieved were evaluated on the basis of participant feedback. Key components of the meeting that were considered successful and important lessons learned are summarized, so that other like-minded researchers with a shared pharmacy practice research interest could consider leveraging funding opportunities to establish other international pharmacy practice research networks.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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; both teacher heads agree on what is shown here.
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".