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Record W2342802836 · doi:10.1057/9781137298737_9

Between Markets and Masses: Food Assistance and Food Banks in South Africa

2014· book-chapter· en· W2342802836 on OpenAlexaff
Sheryl L. Hendriks, Angela McIntyre

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2014
Typebook-chapter
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFood securitySocial protectionUnemploymentSocial securityFood insecurityDevelopment economicsEconomicsCash transfersCashAgricultureFood aidPovertyEconomic growthBusinessEconomic policyGeographyMarket economyFinance

Abstract

fetched live from OpenAlex

Although food security is enshrined in South Africa’s constitution, the pathways to claiming the right to food are made hazardous by poor coordination between social support and food and agricultural policies. While strides have been made in rolling out social benefits in South Africa, principally in the form of means-tested unconditional cash transfers or social grants (including child grants, disability grants and pensions), these and other arguably transitional measures (such as food parcels, drop-in centres, feeding schemes) fail to keep up with urbanization resulting from rural underinvestment, social decline and intractable unemployment. Moreover, the social and economic repercussions of the HIV/AIDS crisis have been far-reaching, with impacts on food security that are still poorly understood. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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: none
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.005
Scholarly communication0.0060.005
Open science0.0000.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.001

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 head0.110
GPT teacher head0.342
Teacher spread0.232 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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