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Record W3129272735 · doi:10.18820/9781928357759/07

The challenges of breastfeeding in poor urban areas in sub-Saharan Africa

2020· book-chapter· en· W3129272735 on OpenAlexaff
Elizabeth Kimani‐Murage, Frederick Murunga Wekesah, Milka Wanjohi, Carolyn Kemunto Nyamasege, Sandrine Mutoni, Teresia Macharia

Bibliographic record

VenueAfrican Sun Media eBooks · 2020
Typebook-chapter
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsMcGill University
Fundersnot available
KeywordsBreastfeedingEnvironmental healthGeographyMedicineSocioeconomicsPediatricsSociology

Abstract

fetched live from OpenAlex

Optimal breastfeeding has the potential to prevent more than 800 000 deaths in children younger than five years; 500 000 neonatal deaths; and 20 000 deaths in women every year. Despite these benefits, evidence from Sub-Saharan Africa shows that breastfeeding practices remain sub-optimal with only 25 per cent of children exclusively breastfed for the first six months, while six per cent of infants in these countries are never breastfed. For example, although the proportion of children who were exclusively breastfed in Kenya improved from 32 per cent in 2008 to 61 per cent in 2014, pockets of suboptimal breastfeeding practices are documented in urban slums. Exclusive breastfeeding in some of the urban slums in Kenya is as low as two per cent, with the age of introducing complementary foods being onemonth post-delivery, while about a third of children are not breastfed within one hour of delivery as recommended by the World Health Organization (WHO).

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.249
Teacher spread0.208 · 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 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

Citations3
Published2020
Admission routes1
Has abstractyes

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