Rethinking access to racial justice: Race discrimination and First Nations peoples
Bibliographic record
Abstract
Aileen Moreton-Robinson, a Goenpul woman from the Quandamooka people, asserts that the 'official' story about racism in Australia is that it exists only in 'small pockets of society or not at all'.First Nations peoples, she claims, tell quite a different story about where, when and how this problem manifests, identifying it as a significant issue with substantial personal and whole-of-community impacts. 1 Various studies and surveys confirm this.As an example, in a 2016 Northern Territory research project, Telling it like it is: Aboriginal perspectives on race and race relations, 64 per cent of the Aboriginal participants reported 'never' or 'rarely' being treated the same as non-Aboriginal people. 2 The Indigenous Legal Needs Project (ILNP) was a national research project looking at First Nations' access to justice in civil and family law areas that ran from 2011-2015.Depending on the jurisdiction in which they lived, between 28 per cent and 41 per cent of ILNP participants identified having encountered race-based discrimination in the previous two years.3 Discrimination was described by participants as long-standing and omnipresent, suffered 'at least once a day, every day'.'You're going to face it no matter where you are … at work, at home, school, wherever'.4 First Nations peoples' experiences of discrimination range from the interpersonal to the institutional, encompassing blatant racial abuse in public spaces, under-and over-policing, being unable to obtain a private tenancy, being unable to access or to retain paid work, as well as having interactions with mainstream systems that continually fail to accommodate cultural and other needs and perspectives.5
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.047 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.009 | 0.021 |
| 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".