Great Moments: Authenticity, Ideology, and the Telling of Medical "History"
Bibliographic record
Abstract
This essay sheds light on present-day pharmaceutical advertisements by looking back to an important early chapter in pharmaceutical company–sponsored promotion: the Great Moments in Medicine and Great Moments in Pharmacy series of commercial paintings produced by Parke, Davis and Company between 1948 and 1964. Beginning in the early 1950s, Parke-Davis delivered reproductions of the Great Moments series to physicians and pharmacies throughout the United States and Canada and funded monthly pull-out facsimiles in key national magazines. The images also appeared in calendars, popular magazines, and "educational" brochures. By the mid-1960s, articles in both the popular and the medical press lauded the Great Moments images for "changing the face of the American doctor's office," while describing the painter, Robert Thom, as the "Norman Rockwell" of medicine. Our analysis uses source material including popular articles about the Great Moments series, existing scholarship, previously unexamined artist's notes, and, ultimately, the images themselves, to explain why these seemingly kitschy depictions attained such widespread acclaim. We show how Great Moments tapped into a 1950s medical climate when doctors were considered powerfully independent practitioners, pharmaceutical companies begged doctors' good graces, and HMOs and health plans were nowhere to be seen. The article concludes by suggesting that the images offer important lessons for thinking about the historically embedded beliefs painted into the many pharmaceutical advertisements that confront present-day doctors, patients, and other consumers.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.059 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".