Avoiding a Celestial Anthropocene Epoch: A Framework for Space Resources Extraction Reclamation.
Bibliographic record
Abstract
As the demand for minerals and metals soars and supplies diminish, mining operations are consuming a larger footprint on the planet and creating more mining wastes. Humans have created an Anthropocene epoch on Earth.\nMining companies are seeking new sources from the depth of the seas to the heavens above. In recent years, mining of the Moon and other celestial bodies has become feasible.\nThis thesis considers the question, ‘What is a logical and defensible legal framework for post-space resources extraction treatment, given terrestrial best practices?’ It does so through a doctrinal and comparative analysis of Australian and Canadian mining laws regarding terrestrial post-resources extraction treatment of the mined area. It also considers international environmental law on sustainable development and outer space law in order to draw together key legal touchstones. The thesis concludes by recommending a framework for protecting the celestial environment, and avoiding a celestial Anthropocene epoch, while ensuring the benefits of space resources extraction are realised by all humankind.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.047 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".