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Record W2974859279 · doi:10.1505/146554819827293187

Access to information and local democracies: a case study of REDD+ and FLEGT/VPA in Cameroon

2019· article· en· W2974859279 on OpenAlex
Sophia Carodenuto

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe International Forestry Review · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTransparency (behavior)Illegal loggingDeforestation (computer science)BusinessCorporate governanceForest protectionCivil societyEnforcementForest degradationReducing emissions from deforestation and forest degradationClimate changeEnvironmental resource managementLoggingEconomicsCarbon stockPolitical scienceForestryFinanceForest managementGeographyLand degradationAgriculture

Abstract

fetched live from OpenAlex

As technological advancements in forest monitoring – such as remote sensing and commodity supply chain tracking – allow for the generation and analysis of increasingly large datasets, forest policy makers and practitioners are looking for innovative yet practical ways for information transparency to transform forest governance. Especially in tropical forest countries looking to address the continuing deforestation and forest degradation through climate finance commitments and timber trade agreements, the access to information agenda has been placed at the fore of both the Reducing Emissions from Deforestation and forest Degradation (REDD+) process and the Forest Law Enforcement, Governance and Trade (FLEGT) Action Plan. This paper explores whether and how the proposed transparency agenda is having an impact (or not) in the Southwest Region of Cameroon. Using semi-structured interviews with civil society organizations, this paper examines how information is currently disclosed in the forest sector and the status of REDD+ and FLEGT transparency agendas at the local level.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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