Raising public awareness of the pharmacists’ involvement in the fight against the COVID-19 pandemic – the effects of Pharmacy Heroes campaign
Bibliographic record
Abstract
Background: The COVID-19 pandemic has significantly impacted health systems around the world. The healthcare burden was visible in all countries struggling with the pandemic. Pharmacists, who are at the frontline beating the COVID-19 pandemic, played a significant role in relieving the burden on healthcare systems. However, the role of pharmacists in the fight against the COVID-19 pandemic was not appreciated. Therefore, our goal was to create the Pharmacy Heroes initiative, which brings together pharmacists from around the world during the COVID-19 pandemic and promotes the role of pharmacists in the health care system. Aim: The article aims to present the results of the Pharmacy Heroes campaign, mainly in terms of dissemination. Results: 85 countries from six continents were involved in the Pharmacy Heroes campaign. Pharmacists who joined the campaign worked in both community and hospital pharmacies. Conclusion: The Pharmacy Heroes campaign showed the significant commitment of pharmacists around the world. Being the third-largest group of medical professionals, pharmacists played a crucial role in fighting the COVID-19 pandemic.
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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 | 0.004 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".