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Record W3096462501 · doi:10.5539/mas.v14n11p9

Participatory Rural Appraisal on Cowpea Production Constraints and Farmers’ Management Practices in Burkina Faso

2020· article· en· W3096462501 on OpenAlexvenueno aff
Adelaїde P. Ouedraogo, Agyemang Danquah, Jean-Baptiste Tignegre, Benoît Joseph Batieno, Herve Bama, Dieudonne Ilboudo, Jeremy T. Ouedraogo, Jonathan N. Ayertey, Kwadwo Ofori

Bibliographic record

VenueModern Applied Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
FundersDeutscher Akademischer Austauschdienst
KeywordsParticipatory rural appraisalStrigaProduction (economics)ScarcityIndigenousAgroforestryIntegrated pest managementCitizen journalismBusinessBiologyAgronomyAgricultureEconomicsPolitical scienceEcology

Abstract

fetched live from OpenAlex

Success of cowpea cultivation requires a strong understanding of production constraints in order to overcome them. It is thus useful to know whether smallholder cowpea growers use modern or indigenous means to overcome these challenges. We completed a participatory rural appraisal (PRA) study to identify current cowpea production constraints and management practices in Burkina Faso. We interviewed 481 cowpea growers (219 women and 262 men) and used a mixed-method design of collecting both qualitative and quantitative data. The results showed that water scarcity, damage due to insects, plant diseases, striga, lack of training, and marketing challenges are the main constraints to cowpea production. Among insects reducing cowpea yield, growers identified aphids as a major pest. However, growers often did not know the biology and incidence of insects in their fields. This study also identified local resistant cowpea varieties in various locations.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.065
GPT teacher head0.283
Teacher spread0.218 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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