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Record W2016501421 · doi:10.4000/vertigo.3047

Savoirs et usages des recrus post-agricoles du pays Betsileo : valorisation d'une biodiversité oubliée à Madagascar

2005· article· fr· W2016501421 on OpenAlexvenueno aff
Stéphanie M. Carrière, H. Andrianotahiananahary, N. Ranaivoarivelo, Josoa R. Randriamalala

Bibliographic record

VenueVertigO · 2005
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Sur les Hautes-Terres malgaches en bordure ouest du « corridor » forestier qui relie le Parc National de Ranomafana à celui d’Andringitra vivent les populations betsileo. Leur économie, mixte, est essentiellement basée sur la riziculture irriguée de bas-fond mais également en partie sur l’élevage extensif et sur la culture en abattis brûlis qui leur permet de produire du vivrier sur les collines (manioc, patate douce, maïs, haricot…). Dans un contexte international qui semble vouloir mettre l’accent sur le rôle écologique mais aussi social et économique des forêts secondaires, cet article met en valeur les principaux savoirs et usages sur les essences qui s’établissent dans les recrus forestiers post-agricoles de cette région. Ces recrus, ou jachères appelées localement kapoka, sont des lieux de collecte privilégiés et ce à différents niveaux (bois de chauffe et bois d’œuvre, plantes médicinales et rituelles, plantes indicatrices de la saisonnalité mais également de la fertilité du milieu). A travers l’analyse des savoirs et des usages de ces espaces situés entre la rizière et la forêt ainsi que des espèces qui les composent, nous montrons également le lien déterminant et ancestral qui peut exister entre une société de riziculteurs, la forêt et ses arbres.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.243
Teacher spread0.211 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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