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Record W299374742

The Tendency to Urban-Farm in Accra: A Cultural Lag-Labor Surplus Nexus

2012· article· en· W299374742 on OpenAlexaboutno aff
Prince Asafu-Adjaye

Bibliographic record

VenueThe Journal of Third World Studies · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsUrban agricultureAgricultureGeographyFood securityNexus (standard)Food processingQuarter (Canadian coin)Economic growthSocioeconomicsAgricultural economicsEconomicsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

With the rapid urban growth rates, a diminishing ability of many countries to feed the increasing national populations, persistent and escalating food prices, urban agriculture is increasingly becoming a food security strategy both at national and household levels (1) INTRODUCTION Globally, urban farming is a fast growing enterprise with about 800 million city farmers whose activities ensure, according to United Nations (UN) statistics, one-seventh of the world's food production. (2) In the developing world, foodstuffs of urban origin crucially reduce the incidence of adult and child malnutrition in fast expanding cities. (3) It is argued that in sub-Sahara Africa. urban farming is a very important activity as it contributes significantly to the provision of food for African urban families, especially the poor families, as well as employment in the informal sector. (4) A significant percent of urban households in this sub-region are engaged in urban farming. It is estimated that in Ouagadougou (Burkina Faso) over a quarter of the households are into urban farming, in Youande (Cameroon), it is 35 percent while it is over a third of households in Kampala (Uganda). (5) In Tanzania and Kenya the prevalence rates of household engagement in urban farming are 68 percent and 63 percent, respectively. (6) In South Africa, urban vegetable production over the past twenty years has significantly increased as sourcing from Africa by supermarkets in Europe has increased with an equally large expansion in retailing in Africa itself. (7) Though deemed a rural activity, farming is ubiquitous in Accra the pinnacle of urbanism in Ghana. In Accra, Ghana's capital, urban farming provides the city with 90 percent of its fresh vegetables. (8) Although urban vegetable production constitutes a substantial quantum of Accra's fresh vegetables, it is mostly the wealthier crass who benefits from such production. (9) In addition to providing a greater proportion of Accra's vegetable requirements, urban farming employs about a thousand people in Accra. (10) agriculture involves cultivating plants, raising animals and fish and growing fungi within a greater metropolitan area or urban centre. (11) Urban agriculture refers to the cultivation of crops at both the subsistence and commercial levels and keeping of livestock in open spaces in urban areas. (12) Therefore urban agriculture involves the activity of tilling the land for cropping purposes or keeping livestock in urban sites for subsistence or commercial objectives. Given that farming in Ghana is deemed a quintessentially rural activity, the visible presence of farm sites in Accra and other urban centers of Ghana generates curiosity. What explains the tendency for some residents of Accra to take up farming instead of non-farm jobs? In explaining the tendency to urban-farm, a dualism of perspectives has emerged. First, the labor surplus model/dependency theory argues that urban farming is an economic venture. (13) On the other hand, urban farming is considered a cultural practice and this perspective is typified by the cultural lag model. (14) This paper endeavors to contribute to the discussion on the incidence of urban farming by specifically looking at open-space vegetable cultivation in Accra. The paper traces the trajectory of urban farming in Accra and discusses access to urban lands for farming. The cultural lag and labor surplus models used in explaining urban farming as well as other models on urban land use are also assessed in the light of the findings of this study. THE TRAJECTORY OF URBAN FARMING IN ACCRA Accra is Ghana's most populous and urbanized city. In 2000, Accra's population was estimated at 1.66 million people with an estimated annual population growth rate of 3.4 percent. (15) At an annual growth rate of 3.4 percent, the current estimate of Accra's population is 2.23 million. However. the population growth rate in North and West Accra is in the region of 10 percent per annum. …

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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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.284
Teacher spread0.251 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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