Why Doesn’t the United States Have National Health Insurance? The Political Role of the American Medical Association
Bibliographic record
Abstract
This study examines the rise of private health insurance in the United States in the post-World War II era.We investigate the role of the American Medical Association (AMA) which financed a campaign against National Health Insurance that was directed by the country's first political public relations firm, Whitaker & Baxter's (WB) Campaigns, Inc.The AMA-WB Campaign had two key components: (1) physician outreach to patients and civic organizations; and (2) mass advertising that tied private insurance to "freedom" and "the American way."We bring together archival data from several novel sources documenting Campaign intensity.We find a one standard deviation increase in Campaign exposure explains about 20% of the increase in private health insurance enrollment and a similar decline in public opinion support for legislation enacting National Health Insurance.We also find suggestive evidence that the Campaign altered the narrative for how legislators and pollsters described health insurance.These findings suggest the rise of private health insurance in the U.S. was not solely due to wartime wage freezes, collective bargaining, or favorable tax treatment.Rather, it was also enabled by an interest group-financed Campaign that used ideology to influence the behavior and views of ordinary citizens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".