Humility as a Core Value for the Adoption of Technology in Medicine: Building a Foundation for Communication and Collaboration
Bibliographic record
Abstract
Humility is a virtue which has been discussed and written about for millennia, among philosophers, religious scholars, and ethicists. From Socrates to Nietzsche, from Roman Catholic traditions to Buddhist writing, thinkers have struggled with defining humility in the human experience, while recognizing its centrality to understanding and relating to the world. Much of the ethos of modern medical education has been influenced by the Flexner report. In the early 20th century, Abraham Flexner visited all medical schools in the United States and Canada to assess and report on the status of medical education for the Carnegie Foundation. Competency-based medical education is influenced by the Dreyfuss and Dreyfuss model of expertise. The master adaptive learner model incorporates phases of planning, learning, assessing, and adjusting in a continuous loop. Humility in the assessing phase allows for more accurate self-assessment and may help mitigate the Dunning–Kruger effect.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".