Bibliographic record
Abstract
Abstract The last few decades have witnessed radical reform of charity regulation around the world. Australia has not been untouched and has developed several unique approaches. First, unlike many other federations (such as the US and Canada), Australia relies on a charities commission rather than its federal tax authority to act as the principal regulator, resulting in a very different scope of responsibility and the likelihood of greater interaction with state regulators. Second, unlike many other jurisdictions that have implemented a charities commission (such as England and Wales), the Australian commission is ultimately intended to apply to a broader pool of not-for-profits than just charities, which raises fundamental questions about the ways in which charities differ from the not-for-profit sector more broadly. This paper outlines the historical and political reasons for reform in Australia and the shape of that reform. As the reforms have now achieved broad political and sector support, the chief focus of this paper is on the out-workings of the reforms, with particular attention to the challenges and opportunities posed by Australia’s federal system of government and by the charity commission’s potential to regulate the broader not-for-profit sector.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".