Considering Canadian Approaches to Equality in the Context of Constitutional Recognition of Aboriginal and Torres Strait Islander Peoples
Bibliographic record
Abstract
Abstract In the context of proposals to amend the Australian Constitution to recognise Aboriginal and Torres Strait Islander peoples, the Expert Panel established by the Australian Government recommended the insertion of a prohibition of racial discrimination. Canadian experiences may assist when exploring the potential implications of prohibiting discrimination in the Australian Constitution and when considering the various options that are available. With this in mind, in this article I discuss the constitutional ideas regarding equality and non-discrimination that have already begun migrating from Canada to Australia and could continue to inform Australian consideration of the numerous issues that may arise. I start with an appraisal of the perceived problems surrounding s 51(xxvi) of the Australian Constitution and the reform options that have already been identified, before considering what Canadian approaches could offer Australia, if anything. My view is that the utility of the transplantation of constitutional provisions depends on the starting point. Its usefulness may be less when the focus is a parochial issue. While it may be possible to draft a tighter prohibition, there could remain a risk that focusing on non-discrimination could overshadow the Aboriginal rights dimensions underlying many calls for recognition.
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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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.031 | 0.027 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".