Successful strategies for native title and Aboriginal cultural heritage approvals—an examination through the development of the Queensland CSG and LNG industry*
Bibliographic record
Abstract
2009 saw an unprecedented level of engagement between oil and gas companies in Queensland and Aboriginal groups, primarily because of Queensland’s burgeoning CSG/LNG industry. Most proponents have had to deal with native title and Aboriginal cultural heritage arrangements with multiple parties simultaneously, often in the early stages of project developments where project certainty is low. Many native title parties have also had to deal with multiple projects at the same time. This has added an extra layer of complexity to what is already a difficult negotiation and regulatory landscape. Queensland and Commonwealth legislation impose a complex system of regulatory approvals governing the interaction of Aboriginal interests and oil and gas projects. Project proponents must comply with state petroleum legislation and Commonwealth native title legislation to ensure approvals are validly granted. This paper will examine the complex legislative and regulatory hurdles that have been faced by project proponents in the Queensland CSG/LNG industry in managing native title and Aboriginal cultural heritage issues. The paper will critically analyse the generally accepted strategies being implemented to address native title and Aboriginal cultural heritage issues. This will include a specific focus on the legal requirements to obtain indigenous land use agreements, the fundamental issues required to be addressed to achieve the authorisation and registration of these agreements, and the alternative options if it is not possible to obtain these agreements. Finally, the paper will conclude with some commentary on the legal aspects of managing Aboriginal cultural heritage.
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 | 0.048 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.022 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".