Federal Land Management: Potential Effects and Factors to Consider in a Move of the Forest Service into the Department of the Interior
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "The Department of Agriculture's (USDA) Forest Service, which manages almost a quarter of the nation's lands, is the only major land management agency outside the Department of the Interior (Interior). Four federal land management agencies--the Forest Service and the Bureau of Land Management (BLM), Fish and Wildlife Service, and National Park Service in Interior--manage most of the 680 million acres of federal land across the country. Growing ecological challenges, ranging from wildland fires to climate change, have revived interest in moving the Forest Service into Interior. GAO was asked to report on the potential effects of moving the Forest Service into Interior and creating a new bureau equal to Interior's other bureaus, such as BLM. GAO was also asked to identify factors that should be considered if such a move were legislated, as well as management practices that could facilitate a move."
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".