Deliberative freedoms and the asymmetric features of anti-discrimination law
Bibliographic record
Abstract
In a series of papers, Sophia Moreau has offered an original and important account of the value underlying anti-discrimination law, which we call ‘the deliberative freedoms account.’ According to this account, anti-discrimination law exists to protect people’s ‘deliberative freedoms’ – that is, their freedom to make decisions about how to live their lives without having to take into account, as a cost, characteristics such as their gender, race, and age. Viewing anti-discrimination law in this way, Moreau suggests, helps explain why the law treats a discriminatory act as a personal wrong against the complainant. It also reveals an underlying unity between different areas of anti-discrimination law, such as direct discrimination, indirect discrimination, and special accommodation requirements. Despite its strengths, we argue that the deliberative freedoms account does not fit well with asymmetrical features of anti-discrimination law – that is, ways in which the law provides protection to one group (for example, people with a disability) but not to an associated group (for example, people without a disability). In particular, we contend that Moreau cannot account for the recognition by anti-discrimination law of legitimate affirmative action policies. This, we argue, provides a powerful reason to reject the deliberative freedoms account. We also consider more recent, largely unpublished work in which Moreau suggests that she may be moving towards offering a pluralist account of anti-discrimination law, according to which the protection of deliberative freedoms is only one of the aims, or values underlying, this area of law. We argue that the difficulties we have identified with the deliberative freedoms account are likely to apply also to a pluralist theory that accords significant weight to the protection of deliberative freedoms.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.050 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".