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Record W4220801585 · doi:10.7202/1087100ar

La place des jeunes africains sur les périmètres irrigués dans un contexte de libéralisation et de partenariat public privé : le cas des jeunes agriculteurs du delta du fleuve Sénégal

2022· article· en· W4220801585 on OpenAlexvenueno aff
El Hadji Malick Sylla, Bruno Barbier, Sidy Mohamed Seck, Mbène Dièye Faye, Tahirou Abdoulaye

Bibliographic record

VenueRevue Jeunes et Société · 2022
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)GeographyAgricultureLand tenureGeneral partnershipPrivate sectorGovernment (linguistics)Work (physics)DeltaPovertyEconomic growthPolitical scienceEconomicsArchaeology

Abstract

fetched live from OpenAlex

This article analyzes different approaches to establishing rural youth in irrigation areas in the Senegal River delta in the context of new hydro-agricultural developments and massive land acquisitions by agrobusiness. Government-led irrigation projects introduced in the 1960s distributed free 0.2-hectare plots of land to young workers from the surrounding region. However, in the 1980s, Senegal took a liberal turn that led to a shift from public-sector to private-sector initiatives. As a result, young workers, who often lack the means necessary to acquire land, have found it much more challenging to pursue farming in irrigation areas. Since 2006, few young farmers have acquired any of the 5,000 hectares of new irrigated farmland developed through programs based on the public-private partnership model. At the same time, agro-industry growth has provided young people with many temporary and precarious employment opportunities. Based on surveys of farmers and agricultural workers in the Senegal River delta, we show how young people find it increasingly difficult to acquire land or secure adequate employment in the agricultural sector. In addition, we demonstrate that access to irrigated land, as opposed to salaried agricultural work, represents the most effective strategy for poverty reduction.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.041
GPT teacher head0.263
Teacher spread0.222 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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