Indigenous language and language rights in Australia after the 'Mabo' (no 2) decision - a poor report card
Bibliographic record
Abstract
This paper investigates one element of the decision in Mabo v Queensland [No 2] (1992) 175 CLR 1, namely Indigenous languages, and whether there has been a transformational shift in the treatment and recognition of Indigenous languages and language rights post-Mabo. The paper considers how central language was to the success and content of the Mabo decision. It then critically analyses language rights and laws in Australia, and how these rights are met, or otherwise, in Australia. Native title has opened a window for language recognition in some circumstances for some native title holders, which has been transformational in practice for some native title holders and symbolically transformational for Australia. Otherwise the Report card for Australia on respectful treatments and recognition of Indigenous languages is very poor. Case-studies in modern-day discrimination against Indigenous language speakers are presented, in the education system, in consultation about Indigenous-specific government initiates, in voting and in the criminal justice system. This is in contrast to comparable nations such as New Zealand and Canada, and requirements under International treaties that Australia has ratified or committed to. The way forward is not technically elusive given successful precedents world-wide. Overcoming hurdles for recognition partly rest with exposing and firmly rejecting socio-political views that Indigenous languages are problems, and naturally becoming extinct. A first step is to improve the Overcoming Disadvantage framework, which is supported by all governments, so that it includes indicators that monitor progress in overcoming discrimination, including overcoming discrimination against Indigenous language speakers. Such indicators need to be informed by a view that Indigenous languages are precious and empowering resources for Indigenous peoples, and indeed all Australians and all of earth's citizens.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".