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Record W2121092237 · doi:10.14214/sf.347

Monitoring and information reporting through regulation: an inter-jurisdictional comparison of forestry-related hard laws

2006· article· en· W2121092237 on OpenAlex

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

VenueSilva Fennica · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBusinessSample (material)Environmental resource managementForestryPolitical scienceLawGeographyEconomics

Abstract

fetched live from OpenAlex

<ja:p>In most jurisdictions, the rule of law has been the core instrument used to implement rules, regulations and restrictions relating to forests. The results of this approach have relied on the effectiveness of the system for regulating through monitoring and reporting. Despite the obvious differences in the wider operating environment of forestry internationally, issues related to globalization have increased the need for comparison. The potential impact of certain social, economic and environmental differences on the nature of monitoring and information reporting is, therefore, important to forest policy and management. The analysis presented here considered data associated with forestry-related monitoring and information reporting to provide a comparative description of certain hard-law requirements in a sample of jurisdictions. This was done to shed light on the potential for coordinated monitoring and information reporting objectives to be mandated through inter-jurisdictional hard law. Our research suggests that further comparative analysis of hard law monitoring and information reporting requirements could form a central theme in defining the ‘ground rules’ of a global forest law.</ja:p>

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 score0.007
Threshold uncertainty score0.324

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 communication0.0000.001
Open science0.0000.000
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 head0.049
GPT teacher head0.310
Teacher spread0.262 · 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