MétaCan
Menu
Back to cohort
Record W4404966796 · doi:10.4000/12tdg

Modèle conceptuel de gestion durable du bassin versant de la rivière Mulet (Haïti) selon l’approche de la recherche-action participative

2024· article· fr· W4404966796 on OpenAlexaff
Zurcher Mardy, Jean‐Philippe Waaub, Sebastian Weissenberger, Ronaldo Joanis

Bibliographic record

VenueNorois · 2024
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversité TÉLUQGDG EnvironnementUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesForestryGeographyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’objectif de ce travail est de coconstruire, sur la base d’un modèle de recherche-action participative préétabli, un modèle de gestion durable du bassin versant de la rivière Mulet (Haïti) dans une perspective d’adaptation aux changements climatiques. De nombreux modèles ont été explorés afin de parvenir à une première conceptualisation, laquelle a été validée par les acteurs locaux engagés pour être adaptée aux réalités du bassin versant. Des entrevues individuelles et de groupe ont été menées au sein de la communauté afin de recueillir des informations sur les aspects relatifs aux savoirs traditionnels et locaux, au système de gouvernance, aux activités économiques, aux systèmes de production, etc. Le modèle obtenu reflète les intérêts, les visions et les apprentissages des différents acteurs impliqués. Ce travail de coconstruction du modèle a également permis de renforcer le capital social des communautés locales tout en améliorant les liens entre les différentes couches sociales du territoire.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.002

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 head0.226
GPT teacher head0.356
Teacher spread0.130 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueNoroisSame topicAgriculture and Rural Development ResearchFrench-language works237,207