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Record W2057133894 · doi:10.1080/17441692.2011.557083

Women's knowledge in Madagascar: A health needs assessment study

2011· article· en· W2057133894 on OpenAlexaff
Evelyn Marion Dell, Susan L. Erikson, Eddy Andrianirina, Gabrielle P. A. Smith

Bibliographic record

VenueGlobal Public Health · 2011
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMedicineEnvironmental healthGeography

Abstract

fetched live from OpenAlex

Nutritional and hygienic practices contribute to high morbidity and mortality rates related to malnutrition in Madagascar. This study, a research effort that brought together charitable organisations, non-governmental organisations (NGOs) and university collaborators, investigates women's health knowledge in the Anosy region of Madagascar. The needs assessment sought to characterise women's knowledge and understanding of nutrition and hygiene. Eight focus groups of 13-60 women each were conducted in the seven most impoverished communes of the Anosy region (n=373). Participants were recruited with the aid of a UK-Malagasy partnered NGO, Azafady. Study findings show that women fully understand the interplay between poor nutrition, hygiene and malnutrition but are unable to change everyday practices because the barriers to better nutrition and hygiene seem beyond their control. These findings may be used to prioritise projects and research seeking to improve nutrition and hygiene, thus reducing malnutrition in the Anosy region.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.085
GPT teacher head0.372
Teacher spread0.288 · 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.

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

Citations4
Published2011
Admission routes1
Has abstractyes

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