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Communicating About Climate Change, Natural Gas Development, and “Fracking”: U.S. and International Perspectives

2016· reference-entry· en· W2499509319 on OpenAlexaboutno aff
Christopher E. Clarke, Dylan Budgen, Darrick Evensen, Richard C. Stedman, Hilary Boudet, Jeffrey Jacquet

Bibliographic record

VenueOxford Research Encyclopedia of Climate Science · 2016
Typereference-entry
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasClimate changePublic opinionFossil fuelRenewable energyNatural resource economicsGlobal warmingHydraulic fracturingEnergy sourceClimate change mitigationNatural gasPolitical scienceBusinessGeographyEconomicsEngineeringLawEcologyPoliticsWaste management

Abstract

fetched live from OpenAlex

Abstract The impacts associated with unconventional natural gas development (UGD) via hydraulic fracturing have generated considerable controversy and introduced terms such as “fracking” into the public lexicon. From a climate change perspective, transitioning from fossil fuels to renewable sources in order to potentially avoid the worst consequences of a warming planet will need to also consider the climate implications of increased UGD and natural gas use that follows. Specifically, how much greenhouse gas is emitted as natural gas is extracted, transported, and consumed relative to other energy sources? Is UGD a “cleaner” energy source? Compared to what? Does it postpone or “bridge” the transition from fossil fuels to renewable energy? Public perception of UGD’s climate impacts not only reflect individual attitudes but broader social discourse among stakeholder groups. Understanding these perceptions, their psychological and social factors antecedents, and how to engage audiences on this topic will play a key role in UGD’s long-term trajectory, especially as it relates to climate change. An added challenge is that most public opinion studies specific to UGD’s climate impacts (and indeed UGD in general) are limited to the United States, Canada, and a few countries in Europe and Africa, with other parts of the world entirely absent. Nonetheless, the studies that do exist highlight several common themes. In particular, UGD tends to be viewed as cleaner relative to fossil fuels because of the belief it produces less carbon emissions as a result of natural gas extraction and consumption. However, it tends to be viewed as dirtier relative to renewables amid the belief that it increases carbon emissions. This finding complements research showing that natural gas occupies a middle ground between renewables and other fossil fuels in terms of acceptance. Moreover, the extent UGD serves as a bridge energy source remains contentious, with some arguing that it and the natural gas it produces complement fossil fuels and facilitates a transition to renewables, while others claim that UGD entrenches society’s continued reliance on the former. Overall, despite the contentious nature of these issues, UGD’s climate impacts appear less salient across countries than other health, environmental, and economic impacts, perhaps because they are psychologically distant and difficult to experience directly. Amid efforts to convey the public health risks associated with a changing climate, we believe that emphasizing the public health dimensions of UGD’s climate impacts can potentially make them more psychologically tangible. Positively framed messages emphasize that reducing carbon emissions tied to both unconventional natural gas extraction and natural gas consumption (relative to other fossil fuels) and thus mitigating the resultant climate change that follows benefits public health. Conversely, negatively framed messages emphasize that increasing carbon emissions (relative to renewables) and thus amplifying the resultant climate change adversely affects public health. At present, though, there is little evidence as to how these messages affect the perceived connection between UGD’s climate impacts and public health and, in turn, support for UGD versus other energy types. Nor is it clear how these outcomes may vary across countries based on public sentiment toward UGD and climate change along with a variety of psychological and social factors that influence such sentiment. Data available for some countries offers tantalizing scenarios, but we remain limited due to the lack of social science research in countries outside the United States and a handful of others. We call for cross-national comparative studies that include places where UGD—and social science research on it—is still maturing.

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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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0020.006
Research integrity0.0000.001
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 head0.037
GPT teacher head0.330
Teacher spread0.293 · 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 designOther design
Domainnot available
GenreReview

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

Citations4
Published2016
Admission routes1
Has abstractyes

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