Bibliographic record
Abstract
Victoria is presently engaged in a process of considering whether to introduce a Bill of Rights. This paper addresses the possibility that any such of Bill of Rights might provide a means for imposing obligations upon the Victorian government to improve the standard of living of people living in poverty. More particularly, in accordance with the government's preference for constraints on the scope of human rights protection, I examine the possibility that an instrument cast in the language of civil and political rights, but not social and economic rights, can meaningfully contribute to the amelioration of poverty. My examination of this possibility takes place from the perspective of experience in Canada with anti-poverty litigation under the Canadian Charter of Rights and Freedoms, which is also cast in the language of civil and political rights. My basic argument is that it is certainly possible that civil and political rights language can be relied upon to impose anti-poverty obligations, but, given the Canadian experience, that possibility is unlikely to be realised in Victoria unless a range of predictable barriers are addressed during the process of establishing a Victorian Bill of Rights. As it happens, the Victorian government's preference for a political, rather than a judicial, supervision mechanism will, perhaps inadvertently, render some of the barriers faced in Canada redundant. But still other barriers will require attention. Those concerned with the plight of the poor and marginalised ought to ensure that the government takes the appropriate action to ameliorate those barriers. In this paper I first briefly describe the process of considering a Bill of Rights established by the Victorian government, giving particular attention to the government's preferred model. This includes consideration of the government's antipathy to including social and economic rights and also an appraisal of the justifications it offers for that position. I then discuss the two approaches that have been used in Canada by those seeking to address poverty through human rights guarantees cast in terms of civil and political rights. I identify the extent to which these approaches have been successful and the barriers to success that have emerged. Finally, I consider the implications of the Canadian experience for a Victorian Bill of Rights.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.041 | 0.031 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.013 | 0.017 |
| 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".