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Record W2280364983 · doi:10.1017/cbo9781316275245

The Affordable Care Act and Medicare in Comparative Context

2015· book· en· W2280364983 on OpenAlexaboutno aff
Eleanor D. Kinney

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Patient Protection and Affordable Care ActHealth insuranceHealth carePolitical scienceState (computer science)Public administrationInflation (cosmology)MedicineActuarial scienceBusinessLawHistory

Abstract

fetched live from OpenAlex

Burdened with perennially rising costs and responsible for providing health insurance to more than one sixth of all Americans, Medicare in its original form is fiscally and demographically unsustainable. In light of dramatic reforms under the Affordable Care Act (ACA), this book provides a comprehensive overview of the current state of Medicare. Eleanor D. Kinney explains how the ACA addresses systemic problems of cost and volume inflation, quality assurance, and fraud. Recognizing the potential for more radical change in the future, Kinney also explores the potential of Medicare to become a single-payer system. Comparisons are made with national health systems in Canada and the United Kingdom, from which the United States can draw valuable lessons. An approachable yet comprehensive account of Medicare and the ACA, this book will be invaluable for health care professionals and informed 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 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)0.003
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0030.006
Scholarly communication0.0080.008
Open science0.0010.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0170.002

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.

Opus teacher head0.071
GPT teacher head0.245
Teacher spread0.174 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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