Intellectual Virtue Vaccination Schedules Need to Include Boosters
Bibliographic record
Abstract
To the Editor: Dr. Ahmadi Nasab Emran1 recently presented a unique approach to the issue concerning physician–pharmaceutical industry interactions. He calls for the development of intellectual virtues early in medical education in order to “vaccinate” against industry influence. This concept has broad implications for how medical information and treatment decisions are translated and shared, but it may not go far enough. With many vaccines, defense against an infection is not guaranteed, but the vaccination nonetheless provides a significant level of protection. In certain cases, the protection offered by the vaccine changes as the environment changes, necessitating updated versions (i.e., booster vaccinations) based on best predictions. Similarly, within medical education, for the development of intellectual virtues to provide the greatest degree of success in protecting against unreliable or biased interpretation of information, programs need to continually update education approaches based on the inevitably changing educational, technological, and informational environment. The core content of teaching in medical education will go a long way to contribute to this inoculation of intellectual virtues. However, the culture within institutions and programs must be such that these fundamentals are supported and fostered. This must go as deep as to view these virtues as essential characteristics addressed in the process of hiring faculty and educators within these programs such that each clinical exposure is consistently reflective of these virtues. Although we desire that virtues be in grained and lifelong, they will potentially fade or become diluted over time. Consid ering the fast-paced practices in which many medical learners will find themselves immersed in the future, inappropriate default behaviors developed peripheral to and during medical education and training can resurface when accessing, evaluating, and translating medical information for clinical care decisions. The need for ongoing “booster vaccinations” for intellectual virtues appears essential. This process needs to begin during medical education by engaging learners in discussions about these virtues and modeling practical ways to maintain them through their careers. The current context of popular continuing professional development programs in corporates relatively little in the way of intellectual virtues. Boosters, however, can be found in a variety of ways through intentionally seeking out the evolving array of high-quality non-industry-sponsored practice conferences, establishing formal faculty mentorships allowing for regular regrounding in evidence-informed practice, and utilizing office-based counter-detailing programs as an alternative to direct industry-sponsored presentations. Seeking out these and other innovative professional development strategies will help to ensure that intellectual virtue maintenance is a reality for future clinicians. Jamison Falk, PharmD Assistant professor, College of Pharmacy and Faculty of Health Sciences, and clinical pharmacotherapy specialist, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada; [email protected]
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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 | 0.007 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".