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Record W4388808726 · doi:10.1016/j.heliyon.2023.e22624

Illuminating practitioner challenges in energy transitions

2023· article· en· W4388808726 on OpenAlexaffabout
Michael Benson, Chad Boda, Runa Das, Leslie A. King, Chad Park

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsEnergy (signal processing)Engineering physicsEngineering ethicsNanotechnologyEngineeringPhysicsMaterials science

Abstract

fetched live from OpenAlex

Sustainable development (SD) is a concept that can be used to address complex challenges, including energy transitions. SD offers diverse strategies that provide useful direction in navigating tensions, trade-offs and synergies in energy transitions. The purpose of this research was to identify the challenges that energy practitioners are faced with in energy transitions and explore potential solutions. To achieve this purpose, we identified and explored the challenges faced by energy practitioners in Canada. Specifically, we conducted a survey of 34 energy practitioners from across Canada, as well as in-depth interviews with the Energy Futures Lab design team (which is a civil society initiative actively working on the energy transition in Canada). We identified the following challenges faced by energy practitioners in Canada: there is no simple, single solution for energy transitions; energy transitions have potentially conflicting considerations; energy systems have potentially conflicting goals; energy practitioners have different levels of trust and competencies in key actors; energy practitioners need to work across the political spectrum; and the costs and benefits of energy transitions are unevenly distributed. We discuss how the three strategies of SD (i.e., economic choice, political choice, social choice) could be applied to manage the intended and unintended tensions and trade-offs inherent in energy transitions. We conclude that the three SD strategies are not always equally valued by energy practitioners, but they have the potential to be useful in different energy transitions scenarios.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.259
Teacher spread0.218 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

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