An Explication of Common Ownership and Common Territory
Bibliographic record
Abstract
Water is the fulcrum on which life pivots—it is nonpareil in its importance for life on Earth. Climate change and the ever-expanding sphere of water commodification raise important ethical and sociopolitical questions and ramifications that are not reducible to only distributional concerns. Philosophical, normative work on climate change is prolific, but there is considerably less research on water issues specifically. Drawing on research in democratic political theory and environmental philosophy, I pose and address five main questions in this book: 1. What right, if any, do people have to water? 2. What are the putative harms of privatizing and commodifying water? 3. Should naturally occurring necessities for human life, like water, be considered owned in common as common territory or property? 4. If so, what are the most compelling normative and ethical grounds for justifying common ownership of water? 5. How might people’s rights to access to water be protected through legal and political means, and what role might local and transnational political activism play in hastening the implementation of such protections? In answering these questions, this book contributes to the burgeoning study of water ethics and justice within academic philosophy while working through the lens of non-ideal theory and a hybrid engaged philosophy. Communities subjected to water commodification, I argue, ultimately suffer a form of political domination insofar as they lack democratic decision-making power and control over this most vital of resources. I contend that deliberative democratic theory provides suggestive tools (at the level of norms and institutional design) for rethinking the governance of water. Drawing on contemporary water justice movements, I also show how anti-water-commodification struggles can utilize water recommoning practices to make water governance processes more deeply democratic. By way of five main case studies—Guelph-Wellington; Detroit, Flint and Baltimore; Cochabamba; Grenoble; and Kerala—I convey the global yet local, or glocal, scope of normative water issues. Additionally, I provide normative analyses of water governance and water injustice, and I show why the political harms of water commodification require democratic remedies.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".