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Record W2052617999 · doi:10.1080/02255189.2010.9669331

De l'encadrement au conseil aux exploitations agricoles familiales: une évolution indispensable pour les zones cotonnières du Tchad et du Cameroun

2010· article· fr· W2052617999 on OpenAlexvenueno aff
Koye Djondang, Michel Havard

Bibliographic record

VenueCanadian Journal of Development Studies/Revue canadienne d études du développement · 2010
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationPacePolitical scienceBusinessWork (physics)Welfare economicsGeographyEconomicsEngineering

Abstract

fetched live from OpenAlex

Abstract The cultivation of cotton has provided an efficient infrastructure for producers in Cameroon and Chad for many generations. However, changes in the cotton industry in recent years (reduced governmental involvement, ongoing crisis) are highlighting the limits of this infrastructure, which is essentially based on disseminating technical information. Producers must now manage the services they need and improve their technical and economic output to keep pace with expanding markets. The issue of support initiatives for farmers is examined, and in particular the work of the Conseil à l'exploitation familiale (CEF) in the cotton-growing regions of these two countries. The CEF supports farmers' efforts to develop conceptual skills in concrete and contemporary subject areas, followed by subjects requiring future planning and conceptualization. A flexible, step-by-step approach is initially used with groups of farmers expressing interest. This approach has improved production methods as well as farmer-seller relations. Qualified staff and appropriate funding are needed to enable development groups to adopt these programs. CEF is designed for organized, stable industries.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.266
Teacher spread0.200 · 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.

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

Citations4
Published2010
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Development Studies/Revue canadienne d études du développementSame topicAgriculture and Rural Development ResearchFrench-language works237,207