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Record W7095165734

HEALTH POLICY Distributive Justice and Infertility Treatment in Canada

2014· article· en· W7095165734 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVeil of ignoranceDistributive justiceEconomic JusticePosition (finance)IgnoranceOriginal positionInfertilityInequality
DOInot available

Abstract

fetched live from OpenAlex

An exploration of distributive justice in Canadian infertility treatment requires the integration of ethical, clinical, and economic principles. In 1971, American philosopher John Rawls proposed a theoretical model for fair decision-making in which “rational ” and “self-interested ” citizens are behind a “veil of ignorance ” with respect to both their own position and the position of other decision-makers. Rawls proposed that these self-interested decision-makers, fearing that they are among the least advantaged persons who could be affected by the decision, will agree only upon rules that encode equality of opportunity and that bestow the greatest benefit on the least advantaged citizens. Regarding health policy decision-making, Rawls ’ model is best illustrated by Canadian philosopher Warren Bourgeois in his panel of “volunteers. ” These rational and self-interested volunteers

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)0.015
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.394
Threshold uncertainty score0.703

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0240.010
Scholarly communication0.0080.002
Open science0.0020.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0110.000

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 head0.032
GPT teacher head0.230
Teacher spread0.199 · 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
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
Published2014
Admission routes1
Has abstractyes

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