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Record W1508186197

Environmental Law for Sustainability

2006· article· en· W1508186197 on OpenAlexaff
Benjamin J. Richardson, Stepan Wood

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsYork University
Fundersnot available
KeywordsEnvironmental lawSustainabilitySustainable developmentPolitical scienceScholarshipPremiseEnvironmental governanceIndigenousLawIndigenous rightsPublic lawState (computer science)Corporate governanceSociologyEnvironmental ethicsHuman rightsManagementEconomicsEcology
DOInot available

Abstract

fetched live from OpenAlex

This volume of new essays presents critical new scholarship on law for sustainable development. Its contributors provide international and comparative perspectives on the current state of environmental law and its future directions. Aimed at both students and scholars in law and other social sciences, it goes beyond conventional descriptions of environmental law and policy to a theoretical and interdisciplinary analysis of the role of law in sustainable development. Starting from the premise that ecological sustainability requires environmental law systems to be sensitive to a wide array of institutional, social and economic issues and to emerging forms of environmental governance beyond conventional legal regulation, the book explores: future directions in command regulation; changing forms of public administration; risk assessment and precautionary regulation; ecological justice; public participation in environmental decision-making; indigenous peoples and the environment; industry self-regulation; economic instruments; sustainable finance; the state of international environmental law; and environmental law in developing countries. [From Environmental Law for Sustainability: A Reader: Osgoode Readers Benjamin J Richardson Hart Publishing]

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.012
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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 designNot applicable
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

Citations96
Published2006
Admission routes1
Has abstractyes

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