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Record W4404469199 · doi:10.29173/alr2794

Lawyers in a Warming World

2024· article· en· W4404469199 on OpenAlexvenueaboutno aff
Carol Liao

Bibliographic record

VenueAlberta Law Review · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsWarming upGlobal warmingClimate changeOceanographyGeologyMedicine

Abstract

fetched live from OpenAlex

Climate change is the great disrupter of humanity, and the Canadian legal profession is at an inflection point. This article begins by briefly outlining the self-governing legal profession’s duties in Canada to uphold and protect the public interest in the administration of justice, including ensuring competencies. It then chronicles, and engages in a comparative analysis of, climate change-related resolutions and actions taken across 15 legal bars, societies, and associations around the world and situates those actions to current measures in Canada. In addressing some of the barriers found within self-regulatory bodies and voluntary associations for Canadian lawyers, the article then provides a basic primer for lawyers to understand the growing significance of climate change impacts on legal systems and civilizations and its potential to undermine legal rights. It identifies further areas of research that are needed regarding legal competencies in understanding climate-related risks and opportunities in relation to lawyers’ duty of care to their clients in Canada. Rapid developments in the law and evolving risk registers in response to a warming world are creating new understandings of what constitutes climate competent lawyering. This article lays the groundwork for further work in climate-related actions for the Canadian legal profession.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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 head0.028
GPT teacher head0.250
Teacher spread0.221 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2024
Admission routes2
Has abstractyes

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