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Record W7038435117

Hydraulic Fracturing Litigation: The Case of Jessica Ernst & the Problem of Factual Causation

2018· article· en· W7038435117 on OpenAlexaboutno aff

Bibliographic record

VenueCanada-United States law journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistic research and analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic fracturingCausationPlaintiffLawsuitLiabilityDirectional drillingTrespassPresumptionFossil fuel
DOInot available

Abstract

fetched live from OpenAlex

Modem hydraulic fracturing technology and horizontal drilling have made it possible and profitable for oil and gas companies to extract natural gas from underground shale and coal formations that would otherwise be inaccessible. Horizontal drilling, in particular, has enabled oil and gas companies to turn under-producing reservoirs into profitable extractive sites. However, despite its technological achievements and economic efficiencies, hydraulic fracturing is not without controversy. One of the main concerns is the potential for groundwater contamination. While experts disagree, the preponderance of evidence suggests that hydraulic fracturing can and has resulted in the unintended toxic contamination of nearby groundwater sources. In the United States, hydraulic fracturing litigation is on the rise, and numerous lawsuits have been filed by landowners against oil and gas companies and regulatory agencies in negligence, nuisance, trespass and the rule in Rylands v. Fletcher for the alleged contamination of their groundwater. In Canada, only one such lawsuit has been filed: Ernst v. EnCana Corp. Common law remedies have proved to be unattainable for most plaintiffs in these cases. The uncertain underground geological consequences of hydraulic fracturing make establishing factual causation a significant legal hurdle. A strict regulatory system that imposes a presumption of liability on oil and gas developers is necessary to encourage safe extractive practices and protect the legal interests of landowners.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
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 studies0.0010.001
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 head0.032
GPT teacher head0.263
Teacher spread0.231 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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