MétaCan
Menu
Back to cohort
Record W2562149941 · doi:10.4000/echogeo.14758

Après le boom : la laborieuse mise en œuvre de nouvelles régulations dans le secteur minier guinéen

2016· article· fr· W2562149941 on OpenAlexaff
Johannes Knierzinger

Bibliographic record

VenueEchoGéo · 2016
Typearticle
Languagefr
FieldEngineering
TopicMining and Resource Management
Canadian institutionsMicrosemi (Canada)Institute on Governance
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Depuis 2003, après une longue phase de libéralisation dans le secteur minier, au moins une douzaine de pays africains ont adopté de nouveaux codes miniers. Cette nouvelle « génération » de codes se distingue visiblement du caractère libéral des précédents. À partir de l’exemple de la Guinée avant et après le boom minier des années 2000, l’article retrace les étapes de la mise en œuvre d’un tel code minier depuis son adoption en 2011 jusqu’aux nouvelles pratiques et leur suivi sur place, en passant par la modification du code minier en 2013 et par l’adoption des textes d’application et l’adaptation des conventions minières existantes.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.127
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.005
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEchoGéoSame topicMining and Resource ManagementFrench-language works237,207