Moon, Inc.: The New Zealand Model of Granting Legal Personality to Natural Resources Applied to Space
Bibliographic record
Abstract
Abstract This article presents a groundbreaking new model for the management of natural resources, introduced into New Zealand (NZ) law in line with the worldview of the indigenous Maori. The article goes on to analyze the model through the lens of the theory of Nobel Laureate Elinor Ostrom and her design principles for managing common-pool resources. Building on this analysis, the article envisages a scenario of applying model under the NZ Act—adapted using Ostrom's theory—to the moon and other space resources and to space habitats. Considering the unsettledness of the debate on the exploitation of space resources and retreat to national arrangements, the article examines whether the model under the NZ Act holds promise for a widely agreed, efficient, and equitable regime for managing space resources and whether it could also be extended to the governance of space habitats. A product of two legal traditions—the common law and that of the indigenous Maori—the NZ Te Urewera Act 2014 is the first statute in the Western legal tradition to grant legal personality to a natural resource—a natural park—and establishes it as something like a common-law corporation. In addition, the Act sets out the usage rights and establishes institutions. The article concludes that the NZ Act satisfies most of Ostrom's design principles and has potential for success. The article therefore continues with an intellectual exercise, applying the model to the moon and other space resources and to space habitats, and tries to appraise the outcome of such an application. However, the article is not necessarily a call to implement the model under the NZ Act to outer space, but rather to consider alternative governance models for space-based governance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".