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Record W4307977141 · doi:10.1007/978-3-030-93072-1_13

Understanding Food Security and Hunger in Xai-Xai, Mozambique

2022· book-chapter· en· W4307977141 on OpenAlexaff
Inês Raimundo, Mary Caesar

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsWilfrid Laurier UniversityBalsillie School of International Affairs
Fundersnot available
KeywordsFood securitySubsistence agricultureOrder (exchange)GeographyContext (archaeology)AgricultureBusiness

Abstract

fetched live from OpenAlex

Abstract The cyclical alternation of drought, cyclones and floods threaten food security for households in rapidly growing coastal cities such as Xai-Xai, Mozambique. Inhabitants of Xai-Xai are highly dependent on urban subsistence agriculture and informal markets in order to guarantee food for their households. Both of these food security strategies have been affected by natural disasters in recent years making it difficult for households to access food. Recent research discussed in this chapter demonstrates that urban households are deprived of basic needs and live under permanent stress manifested by their inability to provide a pot of xima meal on household’s tables. The area around Xai-Xai used to be the granary of the southern Mozambique, but it is no longer able to guarantee that role. A common response among Xai-Xai residents to questions about urban food security is that food security is a concept for experts who do not understand their lived experiences. To them, food security associated with the whole household having enough xima. This chapter examines the concept of food security from the perspective of what really matters to households in the context of extreme events. The chapter integrates the lead author’s reflections on her community’s experiences with hunger and food security during her childhood with recent research on food security in Mozambique. The significance of this method in this instance is, as stated above, to uncover food security experiences that may well escape rigorous quantitative methods.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.261
Teacher spread0.186 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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