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Record W7133160688

Proposal for a National Contraceptive Coverage Plan

2021· article· en· W7133160688 on OpenAlexaboutno aff
Christina Ricci, Kaman Sandhu, Anjali Behal

Bibliographic record

VenueTSpace · 2021
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsFamily planningUniversal designDeveloped countryPopulationMedical prescriptionUnintended pregnancyReproductive healthPlan (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Canada is the only developed country in the world that offers universal medicare, but does not offer coverage for prescription drugs, including contraceptives. Evidence shows that universal contraceptive access has proven to be both economically and socially beneficial in the long-term. Universal contraceptive access usage allows for better family planning, a decrease in the number of high-risk pregnancies, more highly educated women and improved choice in contraceptive type. Long-acting contraceptives are considered the most effective contraceptive method and can last 3-10 years. In 2015, unplanned pregnancies resulted in $320 millions dollars spent for the health care system which is preventable. Improved financial access to contraceptives would be alleviate though that universal contraceptive access but improved physical access to contraceptives is also necessary. A national contraceptive coverage plan that includes long-acting contraceptives is needed at the federal level to reduce unintended pregnancies and empower women.

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)0.008
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.168
Threshold uncertainty score0.334

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0030.004
Research integrity0.0220.012
Insufficient payload (model declined to judge)0.0290.009

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 head0.038
GPT teacher head0.375
Teacher spread0.337 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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