Regulating Energy Innovation: US Responses to Hydraulic Fracturing, Wastewater Injection and Induced Seismicity
Bibliographic record
Abstract
This article focuses on how hydraulic fracturing activities – including wastewater injection – generated, and are still generating, a spectrum of regulatory responses. These regulatory inconsistencies are due to many variables, including: differing opinions on how regulators ought to manage new technologies with unknown environmental impacts; the promise of economic benefit; how politically contested hydraulic fracturing is in the jurisdictions in question; and the fact that much is still unknown about the environmental impacts of hydraulic fracturing. Part I provides an overview of the emerging science on the connections between hydraulic fracturing, wastewater injection and induced seismicity. Part II maps the responses of U.S. state-level regulators to this issue. Part III provides a refresher of the environmental governance theories and practices that help administrative agencies cope with the risks, which energy systems have created, and which agencies are mandated to manage. Part IV evaluates the U.S. state-level responses using the introduced theories and practices. Finally, the conclusion provides some additional reflections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".