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Record W2113807969 · doi:10.12927/hcpap..17352

Clear Goals, Solid Evidence, Integrated Systems, Realistic Roles

2000· review· en· W2113807969 on OpenAlexaffvenueabout
Laurence Thompson

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2000
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsSaskatchewan Canola Development CommissionSaskatchewan Health Authority
Fundersnot available
KeywordsHealth careBusinessNursingPoliticsPreventive careMedicinePolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

To maximize the effectiveness of home care in improving or maintaining the health of Canadians, home-care programs must have clear goals, be founded firmly on evidence of effectiveness, form part of an integrated healthcare system and be grounded in constitutional and political reality. Goals should be client-centred and distinguish between curative, supportive and preventive care. Curative and supportive home care can be cost-effective if substitution for more costly institutional services can be achieved, but the cost-effectiveness of preventive home care and comprehensive care for the elderly has not been clearly demonstrated. Integrated delivery systems are a prerequisite for effective substitution of care at home for institutional care. Federal financing dedicated to a home-care program is unnecessary and is a political and constitutional non-starter. Federal leadership for a national home-care approach would be welcome. Canada Health Act protection for access to medically necessary home care is attractive, but such protection for pharmaceuticals is a higher need. Federal support for research and demonstration of new models of care is valuable.

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)0.073
metaresearch head score (Gemma)0.122
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.073
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.122
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0080.008
Science and technology studies0.0020.010
Scholarly communication0.0100.013
Open science0.0040.005
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0040.002

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 head0.537
GPT teacher head0.495
Teacher spread0.042 · 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
GenreReview

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

Citations6
Published2000
Admission routes3
Has abstractyes

Explore more

Same venueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy→Same topicHealth Systems, Economic Evaluations, Quality of Life→French-language works237,207→