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Record W2108625908 · doi:10.12927/hcpap.2011.22191

The Changing Landscape of Healthcare and Social Policy

2011· letter· en· W2108625908 on OpenAlexvenueaboutno aff
Wendy S. Armstrong

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2011
Typeletter
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careBusinessEnvironmental planningEnvironmental resource managementComputer sciencePolitical scienceGeographyEconomics

Abstract

fetched live from OpenAlex

The problems in traditional residential long-term care settings described in the lead paper are the tip of the iceberg in relation to changes in the landscape of healthcare and social policy in Canada over the past two decades. The primary purpose of this commentary is to identify some of the less visible changes and how these are affecting our perceptions, values and policy directions in "long-term care," however it is defined. The secondary purpose is to caution readers of the dangers of trying to resolve all social policy issues through medicare. This temptation is an artifact of our history and fragmented constitutional powers. It is also due to a well-intended but highly problematic shift in the nature and purpose of public health insurance (and government) in Canada during the 1990s. Without a greater understanding of these and other underlying issues, a pan-Canadian program dedicated to residential long-term care under the upcoming Health Accord risks adding to existing problems. There is also a desperate need for better understanding of the intergenerational needs of Canadian families in relation to healthcare and eldercare.

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)0.007
metaresearch head score (Gemma)0.017
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 score0.905
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0390.044
Scholarly communication0.0140.007
Open science0.0040.005
Research integrity0.0420.049
Insufficient payload (model declined to judge)0.0040.001

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 head0.100
GPT teacher head0.372
Teacher spread0.272 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

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