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Record W2335267659 · doi:10.5539/sar.v5n2p27

Seed Delivery Systems and Farm Characteristics Influencing the Improved Seed Uptake by Smallholders in Northern Ghana

2016· article· en· W2335267659 on OpenAlexvenueno aff
Eunice Etwire, A. Ariyawardana, Miranda Y. Mortlock

Bibliographic record

VenueSustainable Agriculture Research · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsBusinessDistribution (mathematics)Delivery systemAgroforestryAgricultural scienceAgronomyBiologyMathematics

Abstract

fetched live from OpenAlex

The utilisation of improved seeds is reliant on distribution system and farmers’ preferences in using the seed. Primary data were collected from key informant interviews in seed delivery chains and a farmer survey to analyse the northern Ghanaian seed delivery systems and factors influencing the adoption of improved seed by farmers. The seed system in Ghana is made up of three main components; a formal seed system, an informal farmers’ seed system and a quasi-formal seed system. The seed chain starts with breeder seed production by Council for Scientific and Industrial Research (except for imported seed) and ends with the grain farmer as the final consumer. The communication flows between members, strength of relationships and farm characteristics reveled to be affecting the improved seed uptake by smallholders in Northern Ghana. The study highlights the value of strengthening the seed delivery system and improving the availability and accessibility of improved seed varieties.

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)0.000
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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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