Great Lakes Initiative: EPA and States Have Made Progress, but Much Remains to Be Done If Water Quality Goals Are to Be Achieved
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "Millions of people in the United States and Canada depend on the Great Lakes for drinking water, recreation, and economic livelihood. During the 1970s, it became apparent that pollutants discharged into the Great Lakes Basin from point sources, such as industrial and municipal facilities, or from nonpoint sources, such as air emissions from power plants, were harming the Great Lakes. Some of these pollutants, known as bioaccumulative chemicals of concern (BCC), pose risks to fish and other species as well as to the humans and wildlife that consume them. In 1995, the Environmental Protection Agency (EPA) issued the Great Lakes Initiative (GLI). The GLI established water quality criteria to be used by states to establish pollutant discharge limits for some BCCs and other pollutants that are discharged by point sources. The GLI also allows states to include flexible permit implementation procedures (flexibilities) that allow facilities' discharges to exceed GLI criteria. This testimony is based on GAO's July 2005 report, Great Lakes Initiative: EPA Needs to Better Ensure the Complete and Consistent Implementation of Water Quality Standards (GAO-05-829) and updated information from EPA and the Great Lakes states. This statement addresses (1) the status of EPA's efforts to develop and approve methods to measure pollutants at the GLI water quality criteria levels, (2) the use of permit flexibilities, and (3) EPA's actions to implement GAO's 2005 recommendations."
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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.044 | 0.020 |
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".