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Record W2001248740 · doi:10.1086/ahr.113.1.227

ROSEMARY A. STEVENS, CHARLES E. ROSENBERG, LAWTON R. BURNS, editors. History and Health Policy in the United States: Putting the Past Back In. (Critical Issues in Health and Medicine.) New Brunswick, N.J.: Rutgers University Press. 2006. Pp. ix, 364. $24.95

2008· article· en· W2001248740 on OpenAlexaboutno aff
Jeffrey A. Engel

Bibliographic record

VenueThe American Historical Review · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipOmnipresenceHealth careTheme (computing)MedicaidPlague (disease)AmbiguityGovernment (linguistics)HistoryPolitical scienceSociologyLawEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This volume of essays by notable medical and policy historians serves to fill in some of the gaps in our understanding of the historical development of health policy in the United States, correct some common misunderstandings, and in some cases provide an overview of existing literature. Most of the essays synthesize existing scholarship rather than present new material, but in doing so they often clarify ambiguity surrounding such troublesome topics as the evolving place of long-term care in the Medicaid program, the development of emergency room care, and the nature of the growth of federally funded biomedical research. The essays all address several key questions that plague historians of health policy, and which are enumerated by editor Charles E. Rosenberg in one of the book's two introductions. Rosenberg points out that the ambiguous role of markets in allocating health resources, the difficulty of evaluating healthcare outcomes, the “imminence and omnipresence of technological and institutional change, and the problems associated with parallel and uncoordinated systems of government all rise repeatedly in the essays of the volume. While it would be hard to describe the book as having an overarching theme, it is true that these questions and ambiguities arise repeatedly in the book's contents.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0330.025

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.

Opus teacher head0.092
GPT teacher head0.318
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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