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Record W2625953094 · doi:10.1093/jwelb/jwx009

Where ‘shale’ we go from here: opportunities and challenges in shale plays located outside the USA

2017· article· en· W2625953094 on OpenAlexaboutno aff
Don C Smith, Jessica M. Richards, R.J. Colwell

Bibliographic record

VenueThe Journal of World Energy Law & Business · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsLicenseStewardship (theology)BusinessPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

While the ‘shale revolution’ is well underway in the United States, shale development has been slow to non-existent throughout the rest of the world despite a global abundance of shale resources. While energy economics no doubt play a major role in this current state of affairs, this report highlights the fundamental need for two distinct yet intertwined “licenses to operate” — the social license to operate and the legal license to operate — that must be effectively in place before shale development outside the United States can begin to take off. This report first discusses the social license to operate in the global oil and gas industry, and analyzes the roles social media, water stewardship, and governments play in the issuance of the social license to operate. This report next identifies the equally important yet often overlooked role played by the legal license to operate in the global oil and gas industry, and advocates for the adoption of Colorado’s regulatory framework as a means of ensuring an effective and legitimate legal license to operate that augments and reinforces the social license to operate. Having provided the conceptual framework of the social and legal licenses to operate, this report then surveys opportunities and challenges in Algeria, Argentina, Australia, Canada, Mexico, South Africa, and the United Kingdom — all countries with significant shale resources. This report's country-by-country survey seeks to provide fundamental knowledge regarding the above- and below-ground factors that can either influence or inhibit the obtainment of the social and legal licenses to operate in each country, which in turn will drive where the shale revolution will expand to next.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.122
GPT teacher head0.225
Teacher spread0.103 · 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 designTheoretical or conceptual
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

Citations2
Published2017
Admission routes1
Has abstractyes

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