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Record W2103158308 · doi:10.2471/blt.06.039842

Methodological considerations in implementing the WHO Global Survey for Monitoring Maternal and Perinatal Health

2008· article· en· W2103158308 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBulletin of the World Health Organization · 2008
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsWestern University
FundersUnited States Agency for International Development
KeywordsLatin AmericansDeveloping countryEnvironmental healthMedicineGlobal healthScale (ratio)Public healthGeographyEconomic growthNursingPolitical scienceCartography

Abstract

fetched live from OpenAlex

OBJECTIVE: To set up a global system for monitoring maternal and perinatal health in 54 countries worldwide. METHODS: The WHO Global Survey for Monitoring Maternal and Perinatal Health was implemented through a network of health institutions, selected using a stratified multistage cluster sampling design. Focused information on maternal and perinatal health was abstracted from hospital records and entered in a specially developed online data management system. Data were collected over a two- to three-month period in each institution. The project was coordinated by WHO and supported by WHO regional offices and country coordinators in Africa and the Americas. FINDINGS: The initial survey was implemented between September 2004 and March 2005 in the African and American regions. A total of 125 institutions in seven African countries and 119 institutions in eight Latin American countries participated. CONCLUSION: This project has created a technologically simple and scientifically sound system for large-scale data management, which can facilitate programme monitoring in countries.

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.

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 score0.112
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.108
GPT teacher head0.388
Teacher spread0.280 · 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