“Do Bugs Need Drugs?” A community education program for the wise use of antibiotics
Bibliographic record
Abstract
"Do Bugs Need Drugs?" is a community and professional education program designed to address antibiotic resistance by decreasing the inappropriate use of antibiotics. Resources have been developed for physicians, pharmacists, nurses and the public, including children, their parents and caregivers, teachers, employers and workers, and long-term care facilities. There are four key strategies: consistent messaging (e.g., handwashing is the best way to stop the spread of infections); networking (through dedicated committee members who have engaged government ministries, professional organizations, health care organizations, academia, industry and businesses, and community groups); aligning interests (e.g., engaging nursing and medical students to deliver a program on antimicrobial resistance (AMR) to Grade 2 students as part of their community health curriculum); and containing costs (e.g., partnering with other organizations for distribution of materials and sharing administrative and printing costs between the Do Bugs Need Drugs programs in Alberta and British Columbia). There is evidence now of an increased willingness in the scientific and medical community to discuss the risks associated with antibiotic use and of growing public awareness that AMR is linked to misuse and overuse of antibiotics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".