Federal Land Agency Coordination Between the Arizona Department of Transportation, Bureau of Land Management & Federal Highway Administration Creating Synergy Through Partnering Principles By:
Bibliographic record
Abstract
Smooth interaction and effective cooperation between state and federal agencies is critically important to managing and completing major public projects in an efficient and timely manner. Rarely does one see the success or long-term value gained from such cooperation as is evident in the recently completed collaboration in Arizona between the Arizona Department of Transportation, the U. S. Bureau of Land Management, and the Federal Highway Administration. This collaboration created a program for environmental streamlining on a statewide basis. In only it’s first iteration the program facilitated the completion of more than a quarter of a billion dollars worth of federally funded Arizona Department of Transportation highway improvement projects on lands managed by the Bureau of Land Management. This program sets a model for coordination between agencies – specifically between transportation and federal land agencies – that is applicable nationwide. The program was accomplished by work in three areas. First: relationships, processes, and issues were addressed in the geographical area of Arizona where the highway projects were planned (ADOT’s Kingman District and BLM’s Kingman Field Office) with the intent of addressing topics for resolution. Second: a Right of Way
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".