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Record W2623022854 · doi:10.5539/jas.v9n7p186

Farmers’ Perspective on Sociological and Environmental Issues of Urban and Peri-Urban Agriculture: A Case Study from Western and Southern Regions of Sierra Leone

2017· article· en· W2623022854 on OpenAlexvenueno aff
Osman Nabay, Abdul Rahman Conteh, Alusaine Edward Samura, Emmanuel S. Hinckley, Mohamed S. Kamara

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodAgricultureSierra leoneAgricultural economicsProduction (economics)Descriptive statisticsBusinessUrban agricultureSet-asideLoanEconomic growthGeographyEconomicsSocioeconomics

Abstract

fetched live from OpenAlex

The paper examined and brought to the fore the typical characteristic of urban and peri-urban farmers in Freetown and Bo communities which serves as major source of supply of agricultural products into the cities’ markets. The social and environmental aspect and perception of producers involved in urban and peri-urban agriculture was examined. Descriptive statistics and pictograms were used to analyze and present the data. Results indicate that 56.34% never went to formal school and mostly dominated by women, showing that farming became the alternative means of livelihood support for those groups. Crops grown are purely influenced by market orientation—demand and cost, as is evident in Gloucester (lettuce, cabbage and spring onions). Potato leaves were commonly grown in almost all communities, reason being that it serves as common/major sauce/vegetable cooked in every household in Sierra Leone. Maize and rice were featured in Ogoo farm—government supervised land set aside purposely for growing crops to supply the city. Findings also revealed that majority of the farmers are resource poor, judging from calculation about their monthly income earning and available household assets and amenities. About 70.4% of the lands the farmers grow their crops on is leased for production. Except for Gloucester community, when costs of production will be summed, minimal benefit seem to be realized from the farming activities. Even though some of these farmers are engaged in organization, many have limited access to micro financial organization that would probably loan them money to upscale production.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.254
Teacher spread0.233 · 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 designQualitative
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

Citations1
Published2017
Admission routes1
Has abstractyes

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