Rawls and Feminism: What Should Feminists Make of Liberal Neutrality?
Bibliographic record
Abstract
Abstract I argue that Rawls’s liberalism is compatible with feminist goals. I focus primarily on the issue of liberal neutrality, a topic suggested by the work of Catharine MacKinnon. I discuss two kinds of neutrality: neutrality at the level of justifying liberalism itself, and state neutrality in political decision-making. Both kinds are contentious within liberal theory. Rawls’s argument for justice as fairness has been criticized for non-neutrality at the justificatory level, a problem noted by Rawls himself in Political Liberalism. I will defend a qualified account of neutrality at the justificatory level, taking an epistemic approach to argue for the exclusion of certain doctrines from the justificatory process. I then argue that the justification process I describe offers a justificatory stance supportive of the feminist rejection of state-sponsored gender hierarchy. Further, I argue that liberal neutrality at the level of political decision-making will have surprising implications for gender equality. Once the extent of the state’s involvement in the apparently private spheres of family and civil society is recognized, and the disproportionate influence of a sexist conception of the good on those structures—and concomitant promotion of that ideal—is seen, state neutrality implies substantive change. While—as Susan Moller Okin avowed—Rawls himself may have remained ambiguous on how to address gender inequality, his theory implies that the state must seek to create substantive, not merely formal, equality. I suggest that those substantive changes will not conflict with liberal neutrality but instead be required by it.
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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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.063 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".