Mapping the Legal Landscape in Australia, South Africa, Canada and New Zealand and its Applications in the Digital Age
Bibliographic record
Abstract
This chapter maps the legal landscape in Australia, South Africa, Canada and New Zealand, to investigate whether and the extent to which the law in each country prohibits discrimination based on class and/or social background. It finds that whilst ‘class’ and ‘social background’ are not explicitly listed in legislation as grounds of discrimination, the law in each of these jurisdictions lists other grounds of discrimination which include, or reflect, class and/or factors that go to social background. This chapter analyses the law and legal framework in a number of jurisdictions, including: Australia concerning adverse action and termination of employment based on ‘social origin’, and, discrimination based on ‘social origin’; South Africa concerning discrimination based on ‘social origin’; Quebec, New Brunswick and the Northwest Territories concerning discrimination based on ‘social condition’; Canada and various Canadian provinces concerning discrimination based on ‘family status’; and New Zealand concerning discrimination based on ‘family status’.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".