Great Lakes: EPA Needs to Define Organizational Responsibilities Better for Effective Oversight and Cleanup of Contaminated Areas
Bibliographic record
Abstract
A letter report issued by the General Accounting Office with an abstract that begins "To protect the Great Lakes and to address common water quality problems, the United States and Canada entered into the bilateral Great Lakes Water Quality Agreement in 1972. The agreement has been amended several times, most recently in 1987. That year, the two countries agreed to cooperate with state and provincial governments to develop and implement remedial action plans (RAPs) for designated areas in the Great Lakes Basin--areas contaminated, for example, by toxic substances. The Environmental Protection Agency (EPA) leads the effort to meet the goals of the Great Lakes Water Quality Agreement, which include RAP development and implementation. As of April 2002, all of the 26 contaminated areas in the Great Lakes Basin that the United States is responsible for have completed the first stage of the RAP process; however, only half have completed the second stage. Even though EPA has been charged with leading the effort to meet the goals of the agreement, it has not clearly delineated responsibility for oversight of RAPs within the agency, and, citing resource constraints and the need to tend to other Great Lakes priorities, reduced its staff and the amount of funding allocated to states for the purpose of RAP development and implementation."
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 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".