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Record W3119270730 · doi:10.26443/mjm.v17i1.136

Delisting Full Coverage for In Vitro Fertilization in Quebec

2019· article· en· W3119270730 on OpenAlexaffvenueabout
Alexia De Simone

Bibliographic record

VenueMcGill Journal of Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsContext (archaeology)Government (linguistics)MedicineLegislationPaymentHealth careBusinessEconomic growthFinancePolitical scienceGeographyEconomics

Abstract

fetched live from OpenAlex

On 28 November 2015, the Quebec government withdrew full coverage for its assisted procreation program that had been previously covered since 2010. The previously approved legislation under Bill 26 aimed to decrease neonatal intensive-care unit costs associated from multiple birth pregnancies and to increase the number of live-births in the province by funding up to six natural in vitro fertilization (IVF) cycles and implementing a single-embryo-transfer (SET) policy. One factor that contributed to delisting IVF services in Quebec was Quebec’s Commission of Health and Well-Being’s report that concluded that IVF services costed $63 million/per year and resulted in 1300 births/per year. Taken within the larger context of Quebec’s goal to optimize financial ressources within the healthcare system and to reduce the province’s growing debt in 2015, the government withdrew fully-funded IVF services, embryo storage and drug costs and imposed stricter criteria on who could access IVF based on a woman’s age. The government provided tax credits based on a person/couples income, again based on specific criteria. Since implementation of Bill 20, IVF rates have dropped dramatically within the province and multiple-birth pregnancies are on the rise once more. Ultimately, while delisting IVF services in Quebec provided cost-savings in the province’s budget, the law poses serious setbackts to individuals that cannot afford out-of-pocket payments and raises ethical concerns regarding infertility as a medical condition. The newly elected government in 2018 is currently studying the possibility of reinstating full coverage of oneIVF cycle by 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 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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.056
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0360.002

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 head0.041
GPT teacher head0.330
Teacher spread0.289 · 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

Citations0
Published2019
Admission routes3
Has abstractyes

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