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Record W4281701265 · doi:10.5539/enrr.v12n1p37

Farmers’ Perceptions of Land Degradation and Adaptation Strategies Adopted by Farmers in the Geographical Area of Bagaroua in Niger

2022· article· en· W4281701265 on OpenAlexvenueno aff
Abdoulaye Mayara Aichatou, Abdou Gado Fanna, Soumana Boubacar, Barage Moussa

Bibliographic record

VenueEnvironment and Natural Resources Research · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)AgricultureEnvironmental degradationSoil retrogression and degradationGeographyPopulationLand degradationPovertyAgricultural scienceEnvironmental protectionBusinessSocioeconomicsEnvironmental scienceEconomic growthEconomicsEcologyEnvironmental health

Abstract

fetched live from OpenAlex

The study was conducted in the commune of Bagaroua, (Tahoua region). The Tahoua area has agro-climatic characteristics favorable to agricultural production. This area is now threatened by the rapid degradation of its natural resources due to climatic hazards and human activities. It is in this context that the present study proposes to analyze the perceptions of farmers on land degradation and the adaptation strategies of producers faced with the impact of this degradation. The data was collected by interview using a questionnaire submitted to 254 agricultural producers sampled using the formula n=t² *p*(1-p) /m². The results showed that agricultural producers clearly perceive the manifestations of soil degradation by the appearance of glacis with percentages by 66% of respondents; formation of “erosion” ravines (13.17%); presence of pebbles and sandy bulge (10.07%). Farmers perceive the impacts of this soil degradation through parameters such as the reduction in cultivable areas (12%); attacks by crop enemies (7%); increased food insecurity (32%); the influx of able-bodied young people to big cities (11%) inside and outside the country and delinquency (6%). This situation puts the population in a situation of extreme poverty (16%), indebtedness (8%) and conflicts between households (8%). Faced with this shock, producers adopt adaptation strategies, the most widespread of which are, among others, the use of water and soil conservation techniques, the use of organic and mineral manure, the use of improved varieties early.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.254

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 studies0.0000.000
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 head0.025
GPT teacher head0.250
Teacher spread0.225 · 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
Published2022
Admission routes1
Has abstractyes

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