Bibliographic record
Abstract
Hate speech laws have existed in various forms in Australia for well over a decade. Unlike other countries, such as the United States and Canada, they have not faced constitutional hurdles to their existence. The general acceptance of hate speech laws in Australia opens intellectual space for the exploration of a range of interesting questions regarding the laws' operation, the underlying values they pursue and the context within which hate speech is occurring. How should the regulation of hate speech be balanced against Australia's political and cultural commitment to freedom of speech? Who are the hate speakers and how does their speech manifest? What types of hate speech are targeted by existing laws? How are these laws enforced? How can the laws be changed to improve governments' response to hate speech? How does the emergence of bills of rights affect the regulation of hate speech? Drawing on a broad range of academic and practical experts, this book addresses these questions. The essays in first part of this book outline the landscape within which hate speech regulation occurs. They include consideration of the legal, policy and historical context for vilification, the ways in which the language of hatred is changing, and a new look at the longstanding debate about the tension between freedom of speech and hate speech as a conflict between liberty and equality. In part two, the book considers the practice of hate speech regulation in a variety of Australian institutions and includes practical perspectives from the legal profession. In the final part the essays consider hate speech regulation within a broader human rights framework, taking into account the emergence of bills of rights in Australian states.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".