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Record W4388143845 · doi:10.1515/9781773853819

Environment in the Courtroom, Volume II

2023· book· en· W4388143845 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsVolume (thermodynamics)ThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Courts, regulatory tribunals, and international bodies are often seen as a last line of defense for environmental protection. Governmental bodies at the national and provincial level enact and enforce environmental law, and their decisions and actions are the focus of public attention and debate. Court and tribunal decisions may have significant effects on environmental outcomes, corporate practices, and raise questions of how they may best be effectively and efficiently enforced on an ongoing basis. Environment in the Courtroom, Volume II examines major contemporary environmental issues from an environmental law and policy perspective. Expanding and building upon the concepts explored in Environment in the Courtroom, it focuses on issues that have, or potentially could be, the subject of judicial and regulatory tribunal processes and decisions. This comprehensive work brings together leading environmental law and policy specialists to address the protection of the marine environment, issues in Canadian wildlife protection, and the enforcement of greenhouse gas emissions regulation. Drawing on a wide range of viewpoints, Environment in the Courtroom, Volume II asks specific questions about and provides detailed examination of Canada’s international climate obligations, carbon pricing, trading and emissions regulations in oil production, agriculture, and international shipping, the protection of marine mammals and the marine environment, Indigenous rights to protect and manage wildlife, and much more. This is an essential book for students, scholars, and practitioners of environmental law.

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.562
Threshold uncertainty score0.492

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.209
Teacher spread0.188 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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