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Record W4323038565 · doi:10.32920/22212040.v1

Book Review—Environment in the Courtroom by Allan E Ingelson

2023· preprint· en· W4323038565 on OpenAlexafffundabout
Angela Lee

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsUniversity of CalgaryDalhousie University
FundersUniversity of Ottawa
KeywordsParagraphEnvironmental lawLawExecutive directorLibrary sciencePolitical scienceHistorySociologyManagement

Abstract

fetched live from OpenAlex

[First paragraph]: "Environment in the Courtroom, edited by Allan Ingelson (Associate Professor at the University of Calgary and Executive Director of the Canadian Institute of Resources Law), is a recent addition to the literature on Canadian environmental law. The book is a collection of 54 essays that have been presented at national environmental law symposia titled “Environment in the Courtroom” that have been convened on an annual basis in various cities in Canada (specifically, Calgary, Ottawa, and Halifax) over the past seven years.1 A hefty tome of 807 pages, the volume features contributions from 58 authors, which include some of Canada’s leading names in environmental legal academia and practice. On the academic side, this includes scholars like Martin Olszynski, Chris Tollefson, Natasha Affolder, Lynda Collins, and Heather McLeod-Kilmurray, all of whom are professors at faculties of law across the country, and are widely and regularly cited as authorities on a range of environmental issues."

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)0.001
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.128
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0340.016

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 head0.032
GPT teacher head0.325
Teacher spread0.293 · 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
GenreReview

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 routes3
Has abstractyes

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