Regulating Political Advocacy by Charities Liberally
Bibliographic record
Abstract
In countries such as Australia, Canada, the United Kingdom, and the United States, whether certain classes of civil society groups are eligible to receive state support (by way of tax and other concessions) is primarily based on the entity’s intended purpose. Yet governments often view the advocacy, electioneering, or lobbying activities that are the means adopted by some civil society organizations to achieve their purposes, as unjustified attempts to intervene in the political process. Attempts to restrict these activities are, thus, not uncommon but raise challenges to fundamental tenets of liberal democracies. This article uses recent Australian experience as a case study to analyze such attempts through rule of law and freedom of expression lenses. It focuses on advocacy and electioneering via peaceful protest/civil disobedience activities and argues that charities have a valuable role to play as political actors and that any restrictions should meet the requirements of certainty and proportionality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".