How good is Queensland’s Law Reform Commission Inquiry into Mining Lease Objections?
Bibliographic record
Abstract
Publications providing useful analysis of mining law and policy The Queensland Law Reform Commission is reviewing the processes to decide contested applications for mining leases and associated environmental authorities in Queensland. The Commission has published several background papers, providing material and analysis of much broader use that just Queensland law reform. One paper explores key drivers shaping mining’s future: decarbonisation and critical minerals’ demand; rising focus on environmental, social and governance principles; and increasing recognition and respect for First Nations’ rights. Another paper summarises (and compares) the objections processes for mining leases and associated environmental authorities in six jurisdictions: Queensland, Western Australia, New South Wales, Northern Territory, British Columbia (Canada), and South Africa. The Commission’s papers provide excellent summaries and material for anyone wanting to understand mining law and policy processes – what currently exists in these significant mining jurisdictions, and what the future may hold.
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 | 0.028 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 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".