Management Challenges for Aboriginal Cultural Heritage in Peri-urban Queensland
Bibliographic record
Abstract
It is often assumed that places of cultural significance to Aboriginal and Torres Strait Islander peoples are protected under cultural heritage legislation such as the Aboriginal Cultural Heritage Act 2003 in Queensland. Such Acts are improvements on previous policies, which all but neglected Aboriginal cultural heritage. Nevertheless, the aims of policies developed at wider geographic scales, such as States within the Australian system, continue to be disconnected from the experiences of some local Traditional Owners. In this paper, we examine conflicts between non-local policy and on-ground management decisions for Aboriginal cultural heritage in peri-urban Queensland. We focus on the challenges of local Traditional Owners in peri-urban landscapes, basing our discussion on recent experiences conducting research on Indigenous land management in southeast Queensland. We examine three case studies: one in which colonial heritage values were prioritised over existing Aboriginal cultural heritage values, a second where local government failed to support a private landholder’s attempt to identify and protect a cultural heritage site, and a third where a cultural heritage site was protected but in a way that restricts the continuation of cultural practices. Developing more productive and equitable relationships between Traditional Owners and non-Indigenous decision makers, with regards to Aboriginal cultural heritage, requires new locally developed processes for engagement and we suggest how this could be achieved.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".