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Record W2950916131 · doi:10.11575/prism/30045

The Potential Consequences of the Alberta Energy Regulator on Stakeholders in the Resource Industry

2013· dissertation· en· W2950916131 on OpenAlexaboutno aff
Richa Sharma

Bibliographic record

VenueOpen MIND · 2013
Typedissertation
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsRegulatorResource (disambiguation)BusinessNatural resource economicsEnvironmental economicsEnvironmental resource managementEnvironmental scienceEconomicsComputer scienceChemistry

Abstract

fetched live from OpenAlex

The transition to the new regulatory body has significant implications for all those involved in oil, gas, oil sands and coal projects in this Province. Based on the intended goals of the Alberta Energy Regulator (AER) that were derived from the recommendations of the Regulatory Enhancement Task Force, the Province’s new regulator will function differently than the previous three-body system of the Energy Resources Conservation Board (ERCB), Alberta Environment (AE) and Sustainable Resources Development (SRD). This means stakeholders of all kinds must now pay close attention and understand their roles within this new regulatory framework. This paper will evaluate the potential effects of the new regulator on various stakeholders such as the industry, First Nations groups, landowners and environmentalists. This paper will analyze how the system will function differently and where stakeholders can expect to see changes based on available information and analysis of the Responsible Energy Development Act (REDA) and government policies. Given that the new framework is very new, the discussion will necessarily be speculative. However, a good deal can be gleaned from a careful scrutiny of the existing legislation. For the industry, the changes will have significant impacts on the status of their projects. The new regulator has altered the process in which applications are assessed and also changed the procedure for important processes such as hearings and appeals. There is concern that not only will the transition into the new system lead to delays as the new regulator establishes itself, but the process in which applications are submitted and considered will also be altered in ways that will cost the industry through direct and indirect costs.

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)0.018
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.819

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0160.010
Scholarly communication0.0110.005
Open science0.0020.005
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.030
GPT teacher head0.242
Teacher spread0.211 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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