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Record W1979820183 · doi:10.5539/jas.v3n1p128

Vulnerability Profile of Rural Households in South West Nigeria

2011· article· en· W1979820183 on OpenAlexvenueno aff
Abimbola O. Adepoju, Sulaiman Yusuf, B. T. Omonona, Foluso Okunmadewa

Bibliographic record

VenueJournal of Agricultural Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyVulnerability (computing)Psychological interventionSocioeconomicsCentralityPanel dataPanel surveyGeographyPoverty reductionCoping (psychology)EconomicsEconomic growthMedicine

Abstract

fetched live from OpenAlex

This paper examined vulnerability to poverty of households among rural households in South West Nigeria usingprimary data from a two-wave panel survey (lean versus harvesting periods). Results showed that on the averagethere is a 0.56 probability of entering poverty a period ahead in the region and relatively high poverty rates wereassociated with much higher vulnerability while low poverty rates were associated with considerably lowvulnerability. Vulnerable households are mostly large sized with high number of dependants and characterized byunder aged or old, female headed, widowed household heads. They are mostly engaged in farming as their primaryoccupation, have no or low educational attainment and are landless. The findings underscore the centrality ofsocial protection policy mechanisms as potent poverty reduction tools and necessary policy interventions to reduceconsumption variability through reducing exposure to risk or improving the ex post coping mechanisms of thevulnerable.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.266
Teacher spread0.243 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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