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Record W3207669046 · doi:10.1080/09644016.2021.1978199

If it ain’t broke, don’t fix it: how the public’s economic confidence in the fossil fuel industry reduces support for a clean energy transition

2021· article· en· W3207669046 on OpenAlexafffundabout
Christian Schimpf, Brooks DeCillia, Nikita Sleptcov, Melanee Thomas, Lori Thorlakson

Bibliographic record

VenueEnvironmental Politics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of AlbertaUniversity of CalgaryUniversité du Québec à Montréal
FundersCanada First Research Excellence Fund
KeywordsProsperityStatus quoOptimismArgument (complex analysis)Fossil fuelEconomicsNatural resource economicsEconomyBusinessEconomic growthMarket economyEngineeringWaste management

Abstract

fetched live from OpenAlex

We expand on ongoing debates about the role of economic losses and benefits for a clean energy transition. Rather than focusing on the potential economic benefits of alternative industries and energy sources, we highlight the role of economic optimism people display towards the fossil fuel industry. We argue that people’s confidence in the fossil fuel industry to remain an important economic driver in the future can undermine support for climate policies because people do not perceive a need to turn to alternative industries for economic prosperity. Instead, they continue to support the status-quo. We test our argument using survey level data collected in the spring of 2019 in the Canadian province of Alberta, an ideal case due to the province’s economic dependence on the fossil fuel industry. The results support our argument, highlighting the need for policymakers to develop communication strategies on future economic benefits of energy transition.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.993

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.270
Teacher spread0.245 · 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

Citations18
Published2021
Admission routes3
Has abstractyes

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