Bibliographic record
Abstract
Pile repair and replacement are recurring maintenance activities for marine and freshwater ports throughout the United States. Because these activities require in-water work, they trigger the need for environmental permitting and compliance, including Rivers and Harbors Act (RHA) Section 10 and Clean Water Act (CWA) Section 404 permitting with the US Army Corps of Engineers (USACE), as well as compliance with the Endangered Species Act (ESA) and the Marine Mammal Protection Act (MMPA). Preparing individual permit applications for recurring actions of similar scope and with similar potential effects increases uncertainty for project proponents and can affect port operations. It also results in increased costs to project proponents and regulatory agencies alike. To address these issues, federal regulatory agencies, such as the USACE, National Marine Fisheries Service (NMFS), and U.S. Fish and Wildlife Service (USFWS), have developed programmatic permits and consultation processes in which certain types of activities are pre-approved. If a project can be designed to satisfy the criteria of the programmatic approval, then the permit issuance can be expedited. While the USACE has established several existing programmatic permits and ESA consultations, some types of activities do not satisfy the criteria of an existing programmatic permit or ESA consultation. In these cases, a project proponent may be best suited by developing an individual programmatic USACE permit and ESA consultation with NMFS and USFWS, which can be tailored to the needs of the activity. The Port of Tacoma in Washington State recently developed a programmatic CWA permit and ESA consultation for pile replacement at 12 Port facilities for a period of five years. This paper describes the Port's programmatic permitting approach and compares and contrasts it with a traditional approach of permitting individual actions. The paper concludes with a summary of the benefits and potential drawbacks of a programmatic permitting approach, the regulatory considerations, and the types of situations in which a programmatic approach can be most beneficial.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.095 | 0.025 |
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".