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Record W4410049982 · doi:10.1016/j.ijdrr.2025.105549

“If we didn't have anything, not even pots to cook, how do we help each other”: A qualitative analysis of social capital networks and household food access post-cyclone Idai in Beira, Mozambique

2025· article· en· W4410049982 on OpenAlexafffund
Naomi Sunu, Cameron McCordic, Bruce Frayne

Bibliographic record

VenueInternational Journal of Disaster Risk Reduction · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of Waterloo
FundersUniversidade Eduardo MondlaneSocial Sciences and Humanities Research Council of Canada
KeywordsSocial capitalCyclone (programming language)Capital (architecture)Qualitative researchQualitative analysisFisheryAdvertisingBusinessAgricultural economicsEnvironmental healthEconomicsEngineeringSociologyGeographyMedicineBiologySocial science

Abstract

fetched live from OpenAlex

• Bonding and bridging social capital networks facilitated food access among non-displaced households but also deepened post-disaster inequalities. • Linking social capital networks were overwhelmed by Cyclone Idai’s impacts, which limited their facilitation of food access. • Fostering social cohesion between the various social capital networks is crucial for understanding and addressing food insecurity-related disaster risks and impacts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.366
Teacher spread0.336 · 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 designQualitative
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

Citations2
Published2025
Admission routes2
Has abstractyes

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