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Record W2895633143 · doi:10.12927/hcpap.2018.25578

Healthcare Delivery and Physician Accountability in Quebec: A System Ready for Change

2018· article· en· W2895633143 on OpenAlexaffvenueabout
Lawrence Rosenberg

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsThe Quebec Population Health Research Network
Fundersnot available
KeywordsHindsight biasAccountabilityUnintended consequencesLicenseHealth careOrder (exchange)Healthcare systemHealthcare deliveryHealth professionalsPublic relationsHealth care deliveryBusinessNursingMedicinePsychologyPolitical scienceLawSocial psychology

Abstract

fetched live from OpenAlex

In hindsight, there have been unintended systemic consequences stemming from the traditional roles physicians have assumed and the structures within which they have been permitted to organize themselves. It is critical that the national discussion take account of this because we must reconcile ourselves to the current reality in which all other allied healthcare professionals are practising at "the top of their licence." Furthermore, the pace of technological change, especially the deciphering of the genome and the digitalization of virtually everything, has engendered a revolution characterized by the democratization of knowledge and technology, so that the point of care will be wherever the patient is. Dysfunctional reimbursement schemes and a lack of accountability are merely symptoms of a system that must change.

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)0.012
metaresearch head score (Gemma)0.020
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: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.930

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0110.007
Scholarly communication0.0110.004
Open science0.0030.004
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0100.001

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 head0.160
GPT teacher head0.436
Teacher spread0.276 · 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
GenreEmpirical

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

Citations1
Published2018
Admission routes3
Has abstractyes

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