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Record W3160155448

Regulatory Capture and the Role of Academics in Public Policymaking: Lessons from Canada's Environmental Regulatory Review Process

2018· article· en· W3160155448 on OpenAlexaffabout
Jason MacLean

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsUniversity of SaskatchewanUniversity of New Brunswick
Fundersnot available
KeywordsAppealEnvironmental lawPolitical scienceLaw reformSustainabilityPublic administrationProcess (computing)Regulatory reformLaw and economicsLawEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This article proposes an academic law reform model capable of generating viable climate and sustainability policy proposals capable of attracting broad popular appeal. The article unfolds as follows. Following a broad and conceptual Introduction, Part II further unpacks the concept of regulatory capture and the processes by which capture is accomplished, using the Canadian petroleum industry’s capture of environmental law and policy to illustrate how capture works in practice and to ground the novel academic law reform model that is the central contribution of this article. Part III further establishes the need for a novel academic approach to countering capture by briefly examining what this article calls the “catch-22” of regulatory capture reform, and again draws on recent evidence from Canadian environmental law reform efforts as illustration. Part IV, the core of the article, examines Canada’s recent environmental regulatory review process, which concerned the reform of the critically-important federal environmental assessment regime and culminated in Bill C-69 and the new Impact Assessment Act, to advocate for a novel and iterative model of academic law reform capable of countering regulatory capture and generating effective and politically-durable climate and sustainability policies in the public interest. Part V concludes by discussing the limitations of the model proposed here and areas in need of further research.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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 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

Citations5
Published2018
Admission routes2
Has abstractyes

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