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Record W1988543589 · doi:10.4000/vertigo.13811

Dégradation et prédation des boisements communaux avant, pendant et après la guerre au Burundi

2013· article· fr· W1988543589 on OpenAlexvenueno aff
Marc Rwabahungu, Deo Niyonkuru, Libère Bukobero

Bibliographic record

VenueVertigO · 2013
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

La surpopulation, la réduction extrême de la taille des exploitations, la recherche du bois de chauffe et de construction, les nombreux chantiers de reconstruction, la non-exploitation ou l’exploitation insuffisante des autres potentialités énergétiques, l’esprit de pillage, de corruption et de malversation qui ont pris leur envol pendant la guerre sont tous des contraintes majeures qui exposent les boisements communaux et domaniaux à la dégradation. Cet article démontre l’importante d’une bonne gouvernance dans la sauvegarde des boisements communaux et domaniaux. Le fait que les boisements des confessions religieuses n’aient subi de dommages ni avant, ni pendant, ni après la guerre est là pour le confirmer. La population suit en général l’exemple de l’autorité. Même aujourd’hui, les communes où les boisements subissent le plus de dommages sont celles où les autorités communales font montre de moins de sens de responsabilité et s’adonnent aux malversations.

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)0.001
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 score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.280
Teacher spread0.235 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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