Feminist Politics in the Age of Recognition: A Two-Dimensional Approach to Gender Justice
Bibliographic record
Abstract
In the course of the last thirty years, feminist theories of gender have shifted from quasi-Marxist, labor-centered conceptions to putatively “post-Marxist”culture- and identity-based conceptions. Reflecting a broader political move from redistribution to recognition, this shift has been double-edged. On the one hand, it has broadened feminist politics to encompass legitimate issues of representation, identity, and difference. Yet, in the context of an ascendant neoliberalism, feminist struggles for recognition may be serving to less to enrich struggles for redistribution than to displace the latter. I aim to resist that trend. In this essay, I propose an analysis of gender that is broad enough to house the full range of feminist concerns, those central to the old socialist-feminism as well as those rooted in the cultural turn. I also propose a correspondingly broad conception of justice, capable of encompassing both distribution and recognition, and a non-identitarian account of recognition, capable of synergizing with redistribution. I conclude by examining some practical problems that arise when we try to envision institutional reforms that could redress gender maldistribution and gender misrecognition simultaneously.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.074 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| 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".