MétaCan
Menu
Back to cohort
Record W2119969951 · doi:10.1377/hlthaff.19.3.226

The Elderly In Five Nations: The Importance Of Universal Coverage

2000· article· en· W2119969951 on OpenAlexaboutno aff
Karen Donelan, Robert J. Blendon, Cathy Schoen, Katherine Binns, Robin Osborn, Karen Davis

Bibliographic record

VenueHealth Affairs · 2000
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPessimismHealth careEconomic growthPopulationUniversal designDeveloped countryUniversal health careMedicinePolitical scienceEnvironmental healthHealth policyEconomics

Abstract

fetched live from OpenAlex

This paper reports 1999 survey results on the population age sixty-five and older in five nations--Australia, Canada, New Zealand, the United Kingdom, and the United States. The majority of respondents were generally satisfied with the quality, affordability, and availability of health services in their nations. In many measures of access to and cost of care, the United States looks much like the other nations surveyed. However, as the elderly view their health systems, the direction they have taken in recent years with respect to caring for the elderly, and the future affordability of care in old age, U.S. respondents tended to be more pessimistic than were those in other nations.

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)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.387
Teacher spread0.364 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations24
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueHealth AffairsSame topicGlobal Health Care IssuesFrench-language works237,207