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Record W4212855203 · doi:10.3390/su14042213

Sustainable Development and Canada’s Transitioning Energy Systems

2022· article· en· W4212855203 on OpenAlexaffabout
Michael Benson, Chad Boda, Runa Das, Leslie A. King, Chad Park

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsSustainabilityEnergy transitionFutures contractCorporate governanceEnergy (signal processing)Sustainable developmentEnergy engineeringPublic relationsBusinessPolitical scienceSociologyEconomicsManagementEcology

Abstract

fetched live from OpenAlex

An energy transition is unfolding in Canada and across the world. During this transition, countries are facing increasing demands for their energy systems to address economic, social, and environmental considerations, including providing affordable and reliable energy, reducing inequality, and producing fewer environmental impacts. First, we identify key themes from the academic literature related to energy transitions: the systems perspective; economic, social, and environmental considerations; collaboration and dialogue; and social innovation. Second, we focus on a case study of a critical actor in Canada’s energy transition, the Energy Futures Lab (EFL), a social innovation lab that is actively working on the energy transition in Canada. We interviewed members of the EFL design team to investigate and deepen our understanding of the key themes identified in the academic literature. Third, we discuss how our research results relate to innovation and governance in the energy transition in Canada, and we offer an Integrated Model of Sustainable Development (SD) to help manage the common affairs of the energy transition. Fourth, we offer a theoretical contribution, arguing that both the ends and the means should be considered in an energy transition. It is important to keep in mind the overarching objective, or end, of the energy transition (e.g., alignment with the sustainability principles) to create the energy system that the future requires of us. Finally, we offer a practical contribution to show that SD can help inform a collaborative approach, that promotes innovation and increases knowledge, in an effort to address complex sustainability challenges.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 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

Citations10
Published2022
Admission routes2
Has abstractyes

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