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Record W2793886215 · doi:10.4000/echogeo.15192

Développement agricole et gouvernance foncière à Tioroniaradougou (Nord de la Côte d’Ivoire)

2018· article· fr· W2793886215 on OpenAlexaff
Jérôme Aloko-N’Guessan, Marthe Adjoba Koffi-Didia, Hamed Tiécoura Coulibaly

Bibliographic record

VenueEchoGéo · 2018
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsCegep de Saint Jerome
Fundersnot available
KeywordsPolitical scienceCote d ivoireHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La zone de Tioroniaradougou, à l’image des autres régions ivoiriennes, est confrontée à une évolution de la gouvernance foncière traditionnelle. Bien que ces transformations paraissent difficilement conciliables avec les exigences coutumières, elles tendent à se pérenniser sous l’effet du développement agricole conjugué à la pression démographique. La présente étude vise à connaître l’impact du développement agricole sur l’évolution des stratégies de gouvernance foncière à Tioroniaradougou. La démarche adoptée s’appuie sur la recherche bibliographique et l’enquête de terrain. Les résultats obtenus montrent que le développement agricole du terroir est lié à l’essor des cultures de rentes telles que le coton, l’anacarde et la mangue. Avec la diffusion de ces cultures, garantie de revenus certains et réguliers, les paysans établissent des stratégies d’affirmation de leur droit de propriété foncière là où la gouvernance foncière coutumière n’octroie qu’un droit d’usage temporaire. L’instauration du bocage foncier par les paysans constitue également une stratégie d’affirmation des droits d’aliénation sur des ressources foncières limitées.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.004

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 head0.018
GPT teacher head0.292
Teacher spread0.274 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations5
Published2018
Admission routes1
Has abstractyes

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