US Health Policy and Health Care Delivery: Doctors, Reformers, and Entrepreneurs
Bibliographic record
Abstract
From its no-nonsense title to its straightforward conclusion, US Health Policy and Health Care Delivery offers a clear, concise, and informative history of the failure of the United States to establish a system of universal health care. Taking a structural approach, Carl F. Ameringer argues that the system of health care delivery, as it has evolved in the United States, is “poorly equipped and designed to meet the challenges of universal access” (p. 2). In the systems to which Ameringer compares the United States'—those in Australia, Canada, France, Germany, and Great Britain, all of which provide universal health care—the government establishes the frameworks within which doctors and hospitals function. In this country, in contrast, access to health care has been negotiated among “three separate and autonomous policymaking arenas” (p. 13). The professional arena, which principally refers to organized medicine, is controlled largely by doctors. The market arena, which encompasses health systems, insurers, pharmaceutical companies, and nursing homes, is controlled by entrepreneurs and corporate interests. The forces in control in the government arena, which includes legislatures, federal and state agencies, courts, and special interest groups, have been variable, depending on the political climate of a particular era. From the interrelated histories of clashes, negotiations, and compromises within and among each of these three “arenas,” he argues, the American health care system was created, and therein lies its problems.
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 | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.017 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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".