Engaging Colonial Entanglements: “Treatment as a State” Policy for Indigenous Water Co-Governance
Bibliographic record
Abstract
In the United States, treatment as a state (TAS) provisions enable eligible Native American tribes to assume the same responsibilities as state governments in setting and implementing water quality standards (WQSs). Following the introduction of TAS through 1987 amendments to the US Clean Water Act (CWA), forty-four US tribes have enacted TAS tribal standards, which may be more stringent than those of neighboring states; can incorporate cultural and/or ceremonial uses; and can be used to influence pollution levels coming from upstream, off-reservation users. To evaluate TAS as a model for Indigenous water co-governance, we examine how Native American tribes are advancing tribal sovereignty and environmental sustainability through TAS, and we engage with conflicting views on whether and how Indigenous self-determination can be advanced through existing bureaucratic and colonial governance systems. We specifically analyze environmental pollutant listings in tribal water quality standards for the forty-four TAS tribes. Findings suggest that TAS tribes are creating more culturally relevant WQSs, which are typically as comprehensive as, and often more stringent than, analogous state regulations. Tribal standards are diverse, and TAS tribes can set standards independently from neighboring states and one another. Further analysis reveals the complexities of TAS policy, whereby colonial entanglements both enable and constrain enhanced Indigenous self-determination.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".