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Record W2733408849 · doi:10.11575/sppp.v7i0.42472

The Future of Energy Regulation and Policy Development: A Summary Paper

2017· article· en· W2733408849 on OpenAlexaffabout
Shantel Beach, Andrew Wilkins, Jennifer Winter

Bibliographic record

VenueRePEc: Research Papers in Economics · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEnergy (signal processing)Energy policyPolitical sciencePublic economicsEnvironmental economicsEconomicsEngineeringRenewable energyPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In September 2013, The School of Public Policy at the University of Calgary hosted 19 speakers and 55 delegates in Calgary for a full-day symposium entitled “The Future of Energy Regulation and Policy Development: Conflict, Compromise or Cooperation?” Participants included current and past regulatory officials at the federal and provincial or state levels in both Canada and the United States, academics, lawyers active in regulatory matters, and representatives from industry and non-governmental organizations. Symposium chair Michal Moore (Area Director, Energy and Environmental Policy at The School of Public Policy) challenged participants to imagine what the “next regulatory world” would look like and what we want the regulator of the future to look like, and to consider the future success of energy regulation. The discussion on the role and the future of the energy regulator was wide-ranging and thought-provoking. This paper summarizes the discussion and main themes; policy-related implications and observations arising from the symposium are presented in the conclusion.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.282
Teacher spread0.258 · 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 designOther design
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

Citations0
Published2017
Admission routes2
Has abstractyes

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