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Record W4244331613 · doi:10.5539/jas.v6n1p129

The Role of Home Gardens in Household Food Security in Eastern Cape: A Case Study of Three Villages in Nkonkobe Municipality

2013· article· en· W4244331613 on OpenAlexvenueno aff
Ogundiran Oluwasola Adekunle, Nomakhaya Monde, Isaac Azikiwe Agholor, Akinwumi Sunday Odeyemi

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsFood securitySocioeconomicsAgricultural economicsGeographyHousehold incomeAgricultureForest gardeningCapeConsumption (sociology)Production (economics)RevenueEconomicsAgroforestrySociologyBiology

Abstract

fetched live from OpenAlex

Household gardening activities remains an important avenue for food production for most urban and peri-urban populace. The purpose of the study is to examine the relationship between home gardening and household food security in the study area. The specific objectives were to determine the demographic characteristics of farmers in relation to income generated from home garden and examine the role of home garden in household food security. The findings reveals that the mean estimated income earned from vegetable production per year was 473.39 Rand (standard deviation=170.613, N=90), with the mean land size used for farming of 233.60 m2 (standard deviation=31.545, N=90). A correlation between estimated income generated by household per year in Rand from garden produce and land size was conducted to determine whether revenue from gardening could in fact be assessed by land size. Results demonstrated that land size and estimated income generated were positively correlated (r = 0.84, p < .001). In sum, home gardening remains an avenue for enhancing food security, health and social interrelation of households in the contemporary South African society.

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)0.002
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 score0.205
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.218
Teacher spread0.198 · 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 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

Citations16
Published2013
Admission routes1
Has abstractyes

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