BUILDING TRIBAL CAPABILITIES IN ENERGY AND ENVIRONMENTAL MANAGEMENT
Bibliographic record
Abstract
The following activities were completed by the end of the quarter: (1) The CERT Executive Director invited a cross section of CERT member Tribes to participate in the project. By the end of the quarter, three Tribes had the invitation under active consideration, four Tribes expressed interest but wanted to see the detailed workplan prior to making a final decision and one Tribe, the Navajo Nation has accepted the invitation. (2) The CERT Board of Directors Executive Committee has endorsed two significant environmental policy priorities for consideration in the project. First, how does the federal Indian trust responsibility to land and natural resources as well as for the health, safety and political integrity of Indian Tribes affect the federal responsibility for facility cleanup and other statutory mandates under federal environmental statutes? And second, What are the protocols of government-to-government relations within a federal system of shared sovereignty and shared governmental responsibilities? And the corollaries to that question, What is the federal obligation for consultation with Tribes and how is that different and similar to consultation with states? And, What is the federal obligation to work cooperatively with Tribes and states in recognition of the three sovereigns of the American federal system? (3) The CERT consulted with political leaders and environmental staff of member and non-member Tribes. This consultation centered on three environmental policy priorities: issues concerning the intergovernmental interface between states, Tribes and federal government agencies and programs; Issues with the cleanup of federal facilities and activities that have damaged Tribal environmental resources; and issues concerning the DOE cleanup of federal facilities used in the production of nuclear weapons.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 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".