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Record W2023622524 · doi:10.12927/hcpap.2011.22248

Is It Time to Implement a Value-for-Money Approach in Healthcare of the Elderly?

2011· letter· en· W2023622524 on OpenAlexaffvenueabout
Margaret MacAdam

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2011
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsValue (mathematics)Value for moneyHealth careProcess (computing)ScarcityFocus (optics)Public relationsBusinessComputer sciencePolitical sciencePublic economicsEconomicsEconomic growth

Abstract

fetched live from OpenAlex

This commentary addresses several issues raised by Chappell and Hollander in their review of policy issues that should be addressed to improve care for the elderly in Canada. First, the author takes some issue with the suggestion that the continuing care system needs to be re-validated. The data seem to indicate that the issue is not re-validation of the system but, rather, operational reform of the current system. Thus, the recommendation to focus on improving integrated care for seniors, which is a process measure, is a very timely one. Then the author raises the question of recommending a value-for-money approach to care of the elderly. Although fraught with problems and a lack of data, increasing numbers of researchers and others are suggesting that there is a need to question how we are spending scarce resources. A value-for-money policy would contribute evidence about the most effective use of services for older people.

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)0.022
metaresearch head score (Gemma)0.094
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.104
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.094
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0080.009
Scholarly communication0.0080.012
Open science0.0050.004
Research integrity0.1040.077
Insufficient payload (model declined to judge)0.0070.004

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 head0.381
GPT teacher head0.420
Teacher spread0.039 · 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
GenreCommentary

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

Citations2
Published2011
Admission routes3
Has abstractyes

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