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Canada’s Universal Health-Care System: Achieving Its Potential

2018· article· en· W2894832999 on OpenAlexaboutno aff
Danielle Martin, Ashley Miller, Amélie Quesnel‐Vallée, Nadine R. Caron, Bilkis Vissandjée, Gregory P. Marchildon

Bibliographic record

VenueObstetrical & Gynecological Survey · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePrideUniversal coverageUniversal health careUniversal designHealth insuranceHealth careHealthcare systemActuarial scienceNursingHealth policyEconomic growthLawPublic healthBusinessWorld Wide Web

Abstract

fetched live from OpenAlex

(Abstracted from Lancet 2018;391:1718–1735) Canada’s universal publicly funded health care system, known as Medicare, was founded on the principle that access should be determined by need rather than ability to pay. Medicare is an importance source of collective pride in Canada as a universal health coverage model that provides access to physicians and hospital services through 13 tax-funded insurance plans.

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)0.028
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 score0.929
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0060.006
Open science0.0030.009
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0200.002

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 head0.055
GPT teacher head0.369
Teacher spread0.314 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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