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Record W3042572556 · doi:10.12927/hcpap.2020.26262

“You Can’t Get There from Here”: Is There a Future for Value-Based Healthcare in Canada?

2020· article· en· W3042572556 on OpenAlexaffvenueabout
Erin Strumpf

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsHealth careValue (mathematics)Public healthcareWork (physics)Healthcare systemBusinessPublic relationsComputer sciencePolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Moving toward greater value in healthcare in Canada requires more than novel tools and policy levers. First, we need clear objectives, namely, value as defined across stakeholders with primacy given to patients and the public. Next, an unwavering commitment by payers, providers and system managers to pursue those definitions of value. At the most basic level, we need to remember whom the healthcare system is working for. Although numerous pilot projects and promising examples exist, pursuing value in healthcare in Canada will likely require a reassessment of some fundamental aspects of our healthcare systems. A pragmatic approach of learning from the successes and failures of current efforts combined with a major rethinking of the foundational and operating principles of our current systems may be required to get there from here.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.856
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0240.018
Scholarly communication0.0170.008
Open science0.0020.005
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0090.001

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 head0.075
GPT teacher head0.369
Teacher spread0.294 · 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 designTheoretical or conceptual
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

Citations5
Published2020
Admission routes3
Has abstractyes

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