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The Economics of Shale Gas Development

2015· article· en· W3126094046 on OpenAlexaff
Charles F. Mason, Lucija Muehlenbachs, Sheila M. Olmstead

Bibliographic record

VenueAnnual Review of Resource Economics · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBoomExternalityHydraulic fracturingNatural resource economicsEconomicsDirectional drillingProduction (economics)Oil shaleNatural gasUnconventional oilScope (computer science)DrillingEnvironmental sciencePetroleum engineeringMicroeconomicsGeologyEngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

In the past decade, innovations in hydraulic fracturing and horizontal drilling have fueled a boom in the production of natural gas (as well as oil) from geological formations—primarily deep shales—in which hydrocarbon production was previously unprofitable. Impacts on US fossil fuel production and the US economy more broadly have been transformative, even in the first decade. The boom has been accompanied by concerns about negative externalities, including impacts to air, water, and quality of life in producing regions. We describe the economic benefits of the shale gas boom, including direct market impacts and positive externalities, providing back-of-the-envelope estimates of their magnitude. This article also summarizes the current science and economics literatures on negative externalities. We conclude that the likely scope of economic benefits is extraordinarily large and that continued research on the magnitude of negative externalities is necessary to inform risk-mitigating policies.

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: none
Teacher disagreement score0.976
Threshold uncertainty score0.467

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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

Citations95
Published2015
Admission routes1
Has abstractyes

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