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Food Insecurity in the Sub-Saharan Rainlands: Umm Sial, a Village in White Nile State, Sudan

2001· article· en· W144360346 on OpenAlex
Samir Mohamed Ali Hassan Alredaisy, J. L. Davies

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArab world geographer · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsPovertySocioeconomicsGeographyPopulationFood insecurityFood securityWhite (mutation)AgricultureNatural resourceScarcityGovernment (linguistics)Local government areaEnvironmental protectionEconomic growthArchaeologyEconomicsEcologyEnvironmental healthLocal governmentBiology

Abstract

fetched live from OpenAlex

This paper is based upon a survey carried out in 1992 into food security in an environmentally fragile rainland area of the Sudan and reviews the findings relating to Umm Sial, a typical rainland village. It concludes that food insecurity here is the result not only of rainfall unreliability, but also of government neglect, that has resulted in an elderly farming population, with an overrepresentation of females, high levels of child dependency, and considerable poverty. The area is not without natural resources, having considerable grazing potential, but the seriously denuded due to the lack of any coherent policy linking the area with the neigbouring, more prosperous, irrigation lands along the White Nile river.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.204
Teacher spread0.192 · 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