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Record W4414623752 · doi:10.1002/ijgo.70513

FIGO statement on respectful care: Addressing disrespectful maternity care

2025· article· en· W4414623752 on OpenAlexaff
J. Miranda, Hasmik Bareghamyan, Michelle Skaer Therrien, André B. Lalonde, Margit Steinholt, Francesca Palestra, Debra Pascali‐Bonaro, Mindaugas Kliučinskas, María A. Basavilvazo Rodríguez, Garang Ajak, Eliana Amaral, Pius Okong, Birgitta Essén, Bo Jacobsson, Suellen Miller

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsSafeguardingMaternity carePsychological interventionStatement (logic)Health carePrenatal careReproductive medicine

Abstract

fetched live from OpenAlex

The International Federation of Gynecology and Obstetrics (FIGO) Committee on Health Systems Strengthening and Respectful Care recognizes the detrimental effects of disrespectful and abusive practices within maternity care on maternal and neonatal health outcomes. In response, the committee advocates for the implementation of strategic, evidence-based interventions aimed at safeguarding women from substandard and disrespectful treatment during pregnancy, childbirth, and the postpartum period. This statement presents FIGO's recommendations for adopting respectful maternity care into health systems. The proposed policy interventions and clinical strategies are designed to foster compassionate, person-centered, and culturally competent care, thereby contributing to improved maternal and perinatal outcomes globally.

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)0.040
metaresearch head score (Gemma)0.058
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: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.058
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0070.004
Open science0.0080.007
Research integrity0.0610.045
Insufficient payload (model declined to judge)0.0060.005

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 head0.036
GPT teacher head0.401
Teacher spread0.365 · 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
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

Citations2
Published2025
Admission routes1
Has abstractyes

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