The Contributions of First Nations Voices to the Australian Public Debate over the Criminalisation of Coercive Control
Bibliographic record
Abstract
Abstract In Australia, there has been significant public debate over the criminalisation of coercive control and the impact on First Nations women and communities. This debate has included allegations of ‘carceral feminists’ using coercive control to advance a punitive agenda that harms First Nations communities. This article drew on the contributions to the public debate on coercive control by First Nations voices to amplify the views of First Nations women and organisations. The findings of the article identified limited and qualified support for criminalisation by First Nations contributors, with the majority of voices opposed to criminalisation, although both First Nations advocates and critics of criminalisation endorsed the need for alternatives to criminalisation. The article concludes that there is significant work to be done by government and non-indigenous organisations to establish criminal justice and child protection systems trusted by First Nations women and communities.
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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 | 0.038 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.043 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".