MétaCan
Menu
Back to cohort
Record W2577736362 · doi:10.1002/ijgo.12018

Zika virus infection in Brazil and human rights obligations

2016· article· en· W2577736362 on OpenAlexaff
Débora Diniz, Sinara Gumieri, Beatriz Galli Bevilacqua, Rebecca J. Cook, Bernard M. Dickens

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZika virusDeclarationHuman rightsAbortionMicrocephalyPublic healthReproductive rightsPopulationHealth careReproductive healthGovernment (linguistics)LegislationMedicineHarmPolitical scienceEconomic growthEnvironmental healthLawPediatricsVirologyNursingPregnancyVirus

Abstract

fetched live from OpenAlex

The February 2016 WHO declaration that congenital Zika virus syndrome constitutes a Public Health Emergency of International Concern reacted to the outbreak of the syndrome in Brazil. Public health emergencies can justify a spectrum of human rights responses, but in Brazil, the emergency exposed prevailing inequities in the national healthcare system. The government's urging to contain the syndrome, which is associated with microcephaly among newborns, is confounded by lack of reproductive health services. Women with low incomes in particular have little access to such health services. The emergency also illuminates the harm of restrictive abortion legislation, and the potential violation of human rights regarding women's health and under the UN Conventions on the Rights of the Child and on the Rights of Persons with Disabilities. Suggestions have been proposed by which the government can remedy the widespread healthcare inequities among the national population that are instructive for other countries where congenital Zika virus syndrome is prevalent.

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)0.005
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: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.319
Teacher spread0.307 · 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

Citations41
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Gynecology & ObstetricsSame topicGlobal Maternal and Child HealthFrench-language works237,207