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Record W2036580169 · doi:10.5539/sar.v1n1p118

Communication for Sustainable Rural and Agricultural Development in Benue State, Nigeria

2012· article· en· W2036580169 on OpenAlexvenueno aff
A. I. Age, C. P. O. Obinne, Torjape Samuel Demenongu

Bibliographic record

VenueSustainable Agriculture Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicGlobalization and Cultural Identity
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentState (computer science)Agricultural communicationAgricultureDevelopment communicationDecentralizationEconomic growthRural areaPoliticsPolitical scienceSustainable agricultureBusinessSociologyPublic relationsGeographyEconomicsComputer science

Abstract

fetched live from OpenAlex

This discourse discusses communication as a potent sociological tool for rural and agricultural development. It demystifies the concepts of communication, rural and agricultural development. It high-lights principles of communication, types of communication, communication barriers and the role of communication in a holistic and sustainable rural and agricultural development in Benue State, Nigeria. The epilogue concludes by noting that as long as there is continued imbalance in the diffusion of agricultural information and wrongful targeting of information, the possibility of harnessing the full potentials of our rural populace towards attaining sustainable and holistic national, rural and agricultural development will remain problematic and in a limbo and another political snafu. It is recommended that segmentation of the target audience based on needs, interested agro-ecological areas should be adopted by senders of agricultural messages; and decentralization of radio, and television broadcasting in local languages should be encouraged and underscored.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.026
GPT teacher head0.360
Teacher spread0.334 · 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

Citations24
Published2012
Admission routes1
Has abstractyes

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