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Record W2067877588 · doi:10.12927/hcpap.2011.22251

Population Pressures, System-Level Inertia and Healthy Aging Policy Revisited

2011· letter· en· W2067877588 on OpenAlexaffvenue
Andrew Wister

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2011
Typeletter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPopulation ageingContinuum of careInertiaHealth careSet (abstract data type)Medical prescriptionPublic economicsPopulationQuality (philosophy)Health policyQuality of life (healthcare)GerontologyComputer scienceRisk analysis (engineering)BusinessActuarial scienceManagement scienceEconomicsMedicineEconomic growthEnvironmental healthNursing

Abstract

fetched live from OpenAlex

Chappell and Hollander provide support for a set of policy directives formulated for an aging population. An integrated continuum of care model is the fulcrum of the policy prescription, given evidence-based support for its cost-effectiveness; improved quality of care and quality of life; and the success of similar models found in Denmark, Japan and other countries. This commentary addresses the underlying assumptions of these policy recommendations, identifies the major barriers to their implementation and suggests solutions. Improving our understanding of the dynamics of population aging as it relates to health and healthcare use is a necessary requirement to reaching the aims set out by the authors.

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)0.015
metaresearch head score (Gemma)0.029
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 score0.069
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0120.019
Scholarly communication0.0090.011
Open science0.0040.005
Research integrity0.0690.057
Insufficient payload (model declined to judge)0.0070.002

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 head0.125
GPT teacher head0.417
Teacher spread0.292 · 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

Citations3
Published2011
Admission routes2
Has abstractyes

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