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Record W3184257022 · doi:10.4000/vertigo.32010

Réactions et résilience des populations face à la crue de 2012 dans le cinquième arrondissement de Niamey

2021· article· fr· W3184257022 on OpenAlexvenueno aff
Adam Abdou Alou, Céline Lutoff, Harouna Mounkaila

Bibliographic record

VenueVertigO · 2021
Typearticle
Languagefr
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Face à la menace récurrente des crues que subit régulièrement le cinquième arrondissement de la ville de Niamey, cette étude s’intéresse à la manière dont les autorités de la ville et les populations font face aux phénomènes d’inondation. En s’appuyant sur l’inondation exclusive de 2012, elle vise à comprendre les logiques de chacun de ces acteurs dans les stratégies mises en œuvre au moment et à la suite de l’événement. Combinant les approches qualitative et quantitative, l’étude a ainsi permis de mettre en évidence les mesures développées par les autorités de la ville et les individus pour faire face aux événements. Face à l’événement de 2012 et aux dysfonctionnements observés en termes d’alerte et d’évacuation des populations, des mesures de protection active et de prévention passant par le renforcement de la digue de protection de la ville, la relocalisation des populations les plus exposées et l’interdiction de construire en zone à risque d’inondation ont été initiées par les autorités de la ville. Ces mesures ont été complétées par diverses stratégies d’autoprotections individuelles usant des matériaux locaux dans la reconstruction des habitations plus résistantes à l’eau.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.117
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.293
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venueVertigOSame topicFlood Risk Assessment and ManagementFrench-language works237,207