When Fast-Tracking Slows You Down: Reconsidering Nationwide Permit 12 Use for Large-Scale Oil Pipelines
Bibliographic record
Abstract
The consumption of oil pervades everyday life in America. The network of pipelines transporting oil from field to consumer is largely invisible. Until a major news event bursts pipelines onto headlines, this indispensable and invisible system fuels the country without fanfare. At the same time, concern over global climate change has made new large-scale projects for fossil fuel extraction and consumption highly controversial. The Keystone XL (“KXL”) pipeline was originally designed to transport crude oil extracted from oil sands in Canada to the Gulf of Mexico for international export. After more than a decade of false starts, the project currently sits dormant.\nThis Comment uses the battle over the KXL to illustrate the federal framework of interstate oil pipeline regulation in the United States. It examines the preliminary regulatory hoops required for construction and the energy policies gatekeeping key permits. At the heart of the KXL controversy is the United States Army Corps of Engineers’ (“Corps”) permitting program under Section 404 of the Clean Water Act. This Comment critically examines whether the regulatory path of the KXL was appropriate. The KXL sought to fast-track construction by using the Corps’ Nationwide Permit 12, but legal challenges to that permit halted the KXL’s construction.\nThis Comment ultimately recommends that the Corps and the fossil fuel industry stop relying on Nationwide Permit 12 for large-scale pipeline projects. Pipelines longer than 250 miles should instead be individually permitted. Individual permitting would trigger review under the National Environmental Policy Act (“NEPA”), the bedrock environmental law that examines direct and indirect environmental impacts of major federal actions. Comprehensive NEPA review would promote transparency through public input and give the federal government an important foothold in combatting climate change.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.011 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.045 | 0.032 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".