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Record W4401758005 · doi:10.7202/1112469ar

La forêt dans les territoires miniers du Cameroun oriental

2022· article· fr· W4401758005 on OpenAlexvenueno aff
Eric Voundi, Mesmin Tchindjang

Bibliographic record

VenueCahiers de géographie du Québec · 2022
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHumanitiesArt

Abstract

fetched live from OpenAlex

La confrontation spatiale entre des enjeux miniers et la préservation des forêts alimente des controverses dans le Cameroun oriental. Comment le regard sur les mines permet-il de comprendre le lien forêts-communautés ? À partir des théories des parties prenantes et des communs, ainsi que de l’approche de la political ecology , nous analysons les déterminants des controverses autour des forêts en contexte d’exploitation minière dans le Cameroun oriental. Les résultats révèlent que les controverses entre enjeux miniers et forestiers viennent de ce que l’exploitation minière s’additionne à celle des forêts. Le développement peu contrôlé des activités minières entraîne la destruction des ressources forestières sans induire en retour des retombées sociales pour les communautés. Avec l’appui de la société civile, les contestations des populations se multiplient, mettant en cause une gouvernance minière empreinte de corruption, peu à l’écoute des intérêts des communautés et peu propice au développement local durable.

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 score0.148
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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