MétaCan
Menu
Back to cohort
Record W3082095045 · doi:10.5539/sar.v9n4p30

An Overview of the Agricultural Extension System in Egypt: The History, Structure, Modes of Operation and the Future Directions

2020· article· en· W3082095045 on OpenAlexvenueno aff
Ahmed M. Diab, M. Yacoub, Mohamed H. AbdelAal

Bibliographic record

VenueSustainable Agriculture Research · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultural extensionExtension (predicate logic)AgricultureLegislationAgricultural communicationComputer sciencePolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

The main purpose of the current manuscript is to review the agricultural extension system in Egypt. The information gleaned in this article could be useful for policymakers, extension administrators, and extension researchers to identify ways for improving educational services of devising training programs for audience and agents, approaches of farmers' participation, and schemes of policy development. More specifically the objectives of this study are to review the Egyptian agricultural extension system in terms of the: 1) the history of the Egyptian agricultural extension system, 2) the organizational structure of the Egyptian extension system, 3) types of agricultural extension and program delivery mechanisms in Egypt, 4) current situation of the Egyptian agricultural extension system, and 5) the possible future direction for the Egyptian agricultural extension system. A comprehensive review of gray literature was conducted to identify characteristics of the agricultural extension system in Egypt, relevant documents used including, foundation legislation, review and analysis of literature of international organizations as well as peer reviewed journal articles. The extension history, structure, and modes of operation were discussed, and the future directions were concluded.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.318
Teacher spread0.240 · 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 designBench or experimental
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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueSustainable Agriculture ResearchSame topicAgricultural Innovations and PracticesFrench-language works237,207