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Record W2963560605

Privatization and the Future of Canadian Healthcare

2019· article· en· W2963560605 on OpenAlexaffabout
Alexander Babony

Bibliographic record

VenueGlobal Health: Annual Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHealth careOpposition (politics)TaxpayerPoliticsPublic administrationCourageGovernment (linguistics)Political sciencePrivate sectorPublic relationsBusinessLaw
DOInot available

Abstract

fetched live from OpenAlex

The debate over the benefits of public vs private healthcare services in Canada has risen again. While most Canadians agree there should be some form of taxpayer-funded health insurance, disagreements arise over what extent governments should be involved in providing this. In Canada, the prospect of further privatizing healthcare is something few politicians have had the courage to address; it is political suicide. Ontario Premier Doug Ford was recently forced to address leaked documents that (according to the opposition New Democrats) suggested that his administration was intending to implement some degree of private health services in Ontario.1 The public backlash to this was swift and harsh. This article will make the case for opening the healthcare industry to market forces while preserving a separate public system that many in our country currently rely on. It will address the benefits for this rationale from a values-based perspective in an attempt to convince readers on both sides of the political spectrum

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)0.005
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.177
Threshold uncertainty score0.955

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0060.009
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.014
GPT teacher head0.346
Teacher spread0.332 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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