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Record W4406900745 · doi:10.1080/17441692.2025.2456476

Voices and visions: Navigating the landscape of sexual, reproductive, and maternal health and rights in Latin America and the Caribbean: A stakeholder mapping and analysis

2025· article· en· W4406900745 on OpenAlexfundno aff
Sofía Pirsch, Denise Zavala, Mabel Berrueta, María Belizán, Juan Pedro Alonso, Sandra Formia, Jamile Ballivian, Miluska Ramirez-Rodríguez, Maisa Havela, Gabriela Perrota, Analía López, Cintia Cejas, Adolfo Rubinstein

Bibliographic record

VenueGlobal Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsLatin AmericansVisionReproductive rightsReproductive healthStakeholderSexual and reproductive health and rightsGeographyCaribbean regionGender studiesPolitical scienceSociologyPopulationDemographyAnthropologyPublic relationsLaw

Abstract

fetched live from OpenAlex

This article presents the results of a mapping and analysis of key stakeholders operating in the field of Sexual, Reproductive, and Maternal Health and Rights (SRMHR) who are involved in the entitlement of health rights and access to health services for women, adolescents, LGBTQI+ individuals, migrants, indigenous people, Afro-descendants, and people with disabilities in Latin America and the Caribbean. Our study focuses on Argentina, Colombia, Guatemala, Guyana, Jamaica, Mexico, and Peru. The primary objective was to identify and comprehensively categorise the activities undertaken by them, since their actions shape, and promote or hinder the SRMHR political agenda in the region. The findings of this mapping can be useful in contributing to the development of public policy strategies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.339
Teacher spread0.295 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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