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Record W4387168401 · doi:10.24908/qap.v1i1.16425

Obstetric Violence in Developing Health Systems: An Evolving Problem Requiring Novel Intervention

2023· article· en· W4387168401 on OpenAlexaboutno aff
Jayson Pomfret, A Brustolin

Bibliographic record

VenueQapsule Queen s Undergraduate Health Sciences Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsHarmContext (archaeology)Health careDeveloping countryIntervention (counseling)Scope (computer science)Healthcare systemMedicineNursingPsychologyPolitical scienceEconomic growthGeographySocial psychologyLawComputer scienceEconomics

Abstract

fetched live from OpenAlex

While the term obstetric violence has a variable definition given its immensely personal and internally compassionate nature; many accept it to mean: harm inflicted during or in relation to pregnancy, childbearing, and the post-partum period often on the part of a healthcare provider. Obstetric violence, an enigmatic and labyrinthine concern, predominantly and disproportionality affects those experiencing pregnancy in nations with developing healthcare frameworks. The specific comparison that this article will explore is Canada versus Brazil. Due to sociopolitical factors that are beyond the scope of this article, Canada is often seen as a strong representation of developed healthcare whereas Brazil is often placed within the context of developing or underserved as it pertains to healthcare access and development. This is further reinforced by statistical rankings which in 2020 placed Canada as the 15th most developed healthcare system and Brazil ranked at 70.

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)0.015
metaresearch head score (Gemma)0.031
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0080.012
Scholarly communication0.0130.013
Open science0.0050.013
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0170.001

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 head0.091
GPT teacher head0.408
Teacher spread0.317 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueQapsule Queen s Undergraduate Health Sciences JournalSame topicMaternal and Perinatal Health InterventionsFrench-language works237,207