Good and Bad Sharia: Australia's Mixed Response to Islamic Law
Bibliographic record
Abstract
Reflecting on the legal consequences of globalisation in the 21st century, Twining predicted that societies in the West would have to 'wrestle with the extent to which the state should recognise, make concessions to, or even enforce norms and values embedded in different religions, cultures or traditions'. This is borne out as the direction across the common law world moves towards entrenching legal pluralism. The concessions each nation has made to minorities with different religions, cultures and traditions have varied. The special character of Islam, as a comprehensive blueprint for life in which law and religion unite, has meant that the negotiations for a special place for Muslims within each common law jurisdiction has been at the forefront of new legal ordering possibilities. This is the crux of the pluralism debate. Cautiously, Australians have watched the, at times histrionic, discourse in Canada and Great Britain on official recognition for Islamic law.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| 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".