Unincorporated associations as entities : a matter of balance between regulation and facilitation?
Bibliographic record
Abstract
Small non-profit organisations play a vital role in the creation of social capital and resilience of civil society in Australia. A number of government inquiries have recently been commissioned to propose reform to non-profit enterprise and it is timely to examine the suitability of legal structures available for small non-profit organisations. This article reviews the characteristics of small Australian non-profit organisations and the legal treatment of similar associations in New Zealand, the United Kingdom, Europe, Canada and United States to inform possible reform strategies. Reforms are then proposed for small Australian unincorporated organisations which allow them access to the benefits of separate legal entity status, but with regulation proportionate to the risks posed to the broader community.
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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 | 0.019 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".