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Record W2770447749

Agricultural polices and food security : impact on smallholder farmers in Northern Ghana

2017· article· en· W2770447749 on OpenAlexfundno aff
Aburinya Emmanual Azechum

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2017
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
FundersDalhousie UniversityFaculty of Graduate Studies and Research, University of AlbertaSt Mary's University
KeywordsFood securityAgricultureBusinessAgricultural economicsAgricultural productivityNatural resource economicsGeographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Impact on Smallholder Farmers in Northern GhanaGhana's government over the years has adopted and implemented several agricultural polices and programmes with the overall objective of stimulating agricultural growth and enhancing food security.This thesis uses the Oxfam model to assess the impact of agricultural policies on food security among smallholder farmers in northern Ghana.It argues that government agricultural policies have failed to a have positive impact on food security among smallholder farmers in northern Ghana because they were more geared towards promoting the large scale commercial agricultural sector than the smallholder agriculture sector.This claim is supported by the data in Ghana which proves that food insecurity is still a major problem among smallholder farmers in northern Ghana despite the policies and programmes put in place to tackle it.The analysis is based on two main sets of data: national agricultural policies and regional policies from 1980 to 2000.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.310
Teacher spread0.267 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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