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Record W1856811789 · doi:10.5539/jsd.v8n9p71

Trends and Policy Correlates of Agricultural Production and Agricultural Production Sustainability Outcomes in Ghana and Nigeria

2015· article· en· W1856811789 on OpenAlexvenueno aff
Olawale Emmanuel Olayide, Isaac K. Tetteh, Labode Popoola

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersKwame Nkrumah University of Science and TechnologyAfrican Academy of SciencesDepartment for International Development
KeywordsAgricultureSustainabilityAgricultural productivityProduction (economics)Agricultural policyBusinessSustainable developmentDilemmaAgricultural economicsNatural resource economicsEconomic growthEconomicsPolitical scienceGeography

Abstract

fetched live from OpenAlex

This paper analysed policy correlates of agricultural production and agricultural production sustainability outcomes in Ghana and Nigeria. It underscores the influence of political systems and international development agendas as correlates of agricultural production and agricultural production sustainability outcomes. This is to the extent of providing evidence policy on agricultural production and agricultural production sustainability outcomes. Ghana and Nigeria have comparable farming/agricultural system and policy environment. Data used for the analyses spanned five decades. Trends analysis and inferential statistics were employed. The results revealed that policy correlates can contribute to the current discourse in sustainable development agenda and to resolving the dilemma of agricultural policy implementation for sustainable agricultural development, especially in Ghana and Nigeria. The findings reinforce the need for appropriate policies in transforming the agricultural sector while ensuring sustainable development outcomes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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