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Record W1599253449

Health Care Spending: What the Future Will Look Like

2006· preprint· en· W1599253449 on OpenAlexaboutno aff
Laurence J. Kotlikoff, Christian Hagist

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPer capitaGross domestic productHealth careGovernment (linguistics)Economic growthBusinessGovernment spendingPer capita incomeMeasures of national income and outputDevelopment economicsEconomic policyEconomicsEnvironmental healthPopulationMedicine
DOInot available

Abstract

fetched live from OpenAlex

European critics of the U.S. health care system often focus on the private provision of health care and health insurance. Yet the more important difference between the United States and other developed countries is the failure to control government spending. Other countries employ global budgets and control access to expensive drugs and new technology. The United States, by contrast, has very meager spending controls. If current trends continue, U.S. government health care spending will consume an ever growing portion of national income — far more so than any other developed country. Government health care expenditures have grown much more rapidly than the economy in all developed countries. Between 1970 and 2002 these expenditures per capita grew at almost twice the rate of gross domestic product (GDP) per capita in 10 countries studied: Australia, Austria, Canada, Germany, Japan, Norway, Spain, Sweden, the United Kingdom and the United States.

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)0.009
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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0110.017
Open science0.0010.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0190.005

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 head0.049
GPT teacher head0.446
Teacher spread0.396 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicGlobal Health Care IssuesFrench-language works237,207