Is Water Simply a Flow? Exploring an Alternative Mindset for Recognizing Water As a Legal Person
Bibliographic record
Abstract
“Water is a flow that transcends the human-nature binary” (Cohen, 2015), and therefore should be considered accordingly. Our modern societies must deal with severe water issues on a daily basis. These contemporary problematics, although acknowledged through the work of scientists, remain a “headache” for human and social sciences. Indeed, the instruments and mechanisms provided by water law often lack effectiveness. However, in a recent past, judges from India and Colombia, as well as a legislation in New Zealand recognized rivers as a legal person. Moreover, a recent lawsuit (September 2017) was filed in the U.S., asking the District Court in Denver to recognize the Colorado River as a legal person. These judicial innovations constitute an alternative avenue to (re)think the relationship between Humans and Nature, as well as an original tool to protect and preserve our environment. Why don’t we broaden this emerging dialogue by exploring the potential applicability of the legal personality status to water as an entity? More precisely, the following questions could be discussed: (1) Why can water be conceived as a person? (2) Is the concept of legal personality truly extendable to water? And consequently, to what extent can water be considered as a legal person? In order to answer these interrogations, it is firstly essential to describe the theoretical and philosophical grounds that support the idea of thinking of water as a (legal) person. This exercise of “reconceptualization”, based on environmental ethics, examine interactions between human beings and water, along with how they influence the understanding we have of this resource. Secondly, so as to extend this status to water, can we deduct general criteria, from both Common and Civil Law, to define the concept of legal personality? By combining a philosophical and legal approach, we could ultimately aim to explore why water can be treated as a legal person and define under what circumstances this can happen.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.088 |
| Scholarly communication | 0.015 | 0.034 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".