The Next Frontier: An Overview of the Legal and Environmental Implications of Near-Earth Asteroid Mining
Bibliographic record
Abstract
With dwindling terrestrial resources, near-Earth asteroid (NEA) mining may soon become the next frontier in international space exploits and resource exploitation. NASA has already predicted that it will send astronauts to NEAs by 2025, and several other private-entity corporations like Planetary Resources are also taking part in the new space race. Near-Earth mining has the potential to supplement the Earth with much-needed resources, such as, freshwater, rare Earth minerals and oil. Now that mining is technologically and economically feasible, the only impediment seems to be the framework of international space law regimes, such as the Moon Agreement and the Outer Space Treaty. These treaties are archaic in the sense that they were created in a time when near-Earth mining was unfathomable. Accordingly, there are legal ambiguity and interpretation issues which must be resolved prior to commencing space exploits, in order to reduce litigation and conflict. The environmental consequences of near-Earth mining must also be explicitly ascertained, with regard to prevention and mitigation. This will ensure that private-entities who seek to exploit near-Earth asteroids thwart legal and environmental barriers. Thus, the legal uncertainty surrounding near-Earth asteroid appropriation must be clarified to permit appropriate investment, promote terrestrial conservation, prevent geopolitical conflicts and improve living standards through intra- and inter-generational equality for all individuals and nations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".