The Legal Geographies of Water Claims: Seawater Desalination in Mining Regions in Chile
Bibliographic record
Abstract
The use of desalination has been increasing in recent years. Although this is not a new technology, its use often proceeds within ill-defined and ambiguous legal, institutional, economic and political frameworks. This article addresses these considerations for the case of Chile, and offers an evaluation of legal ambiguities regarding differences between desalinated water and other freshwater sources and associated consequences. This discussion reviews court records and legal documents of two companies operating desalination plants, both of which have simultaneous rights granted for underground water exploitation: the water supply company in the Antofagasta Region and Candelaria mining company in the Atacama Region. The analysis shows that issues of ambiguity and gaps in the legal system have been exploited in ways that allow these entities to continue the use and consumption of mountain water. They do so by producing desalinated water, and by entering into water transfer and diversion contracts with the mining sector. These findings highlight the importance of undefined socio-legal terrain in terms of shifting hydro-geographies of mining territories, contributing conceptually to critical geographies of desalination, delineating the importance of legal geographies important for water governance, as well as empirically documenting the significance of this case to consider shifts for the mining sector and water technologies and uses in contemporary Chile.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".