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Record W4313440815 · doi:10.18584/iipj.2022.13.3.10696

Economic Recovery in Response to Worldwide Crises: Fiduciary Responsibility and the Legislative Consultative Process with Respect to Bill 150 (Green Energy and Green Economy Act, 2009) and Bill 197 (COVID-19 Economic Recovery Act, 2020) in Ontario, Canada

2022· article· en· W4313440815 on OpenAlexafffundvenueabout
Stephen R. J. Tsuji

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsFiduciaryIndigenousContext (archaeology)Government (linguistics)DutyLawLegislaturePolitical scienceBusinessPublic administrationHistory

Abstract

fetched live from OpenAlex

The Green Energy and Green Economy Act (2009) was an omnibus bill that affected a number of other acts. Due to the breadth of its effects, it should have seen a rigorous consultation and review process; this is especially true given how it would impact First Nations and its explicit mention in the Bill. However, it took less than three months for it to receive Royal Assent and become an act. This timeline is extremely short, even among similar bills within the same context. One of the core reasons for this swift transition is due to its labeling as green energy, which has benign connotations. This effectively allowed the bill to be expedited through the consultation process. The consultation process had many hurdles of its own that inhibited meaningful consultation including its timeframe, location of hearings, accessibility, and other factors. The term green energy was also never defined within the Act, meaning it only served as a form of signaling. This raises many questions with respect to the Government of Ontario’s conduct in the situation and how they handled their legal duty to consult with Indigenous people of Ontario, Canada. There are many voices that have raised issues with this process. If nothing else, this example serves the purpose of demonstrating the dangers of green-labelling, especially to Indigenous people of Canada and other Indigenous groups worldwide.

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)0.003
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.298
Teacher spread0.282 · 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
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

Citations4
Published2022
Admission routes4
Has abstractyes

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