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Record W4281868050 · doi:10.12927/hcpol.2022.26831

New Spending Programs and Old Frustrations: Where Is the Vision?

2022· article· en· W4281868050 on OpenAlexvenueaboutno aff
Jason M. Sutherland

Bibliographic record

VenueHealthcare policy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
Fundersnot available
KeywordsPrime ministerTaxpayerGovernment (linguistics)Health careCoronavirus disease 2019 (COVID-19)ClearingPolitical scienceAssertionPublic administrationBusinessLawFinanceMedicinePolitics

Abstract

fetched live from OpenAlex

The spring has ushered in an unexpected number of major health policy announcements compared with the last 10 years. They are led by the federal government's outlines of a national pharmacare program, an unexpected dental care program (Prime Minister of Canada Justin Trudeau 2022), plus "top-up" funding for clearing provincial surgical and imaging backlogs. These announcements are on top of the voices expressing concerns about COVID-19-related healthcare expenditure trends (Bailey 2022). Without a doubt, taxpayer money is flowing freely into healthcare (Labby 2020).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.572
GPT teacher head0.594
Teacher spread0.023 · 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 teacher head, not a consensus.

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
Published2022
Admission routes2
Has abstractyes

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