Bibliographic record
Abstract
In this article I examine one of the thorniest aspects of the relationship between feminism and postmodernism, in order to see what a discursive analytic approach can contribute to this important debate. The problem I refer to concerns the threat that the postmodern turn-despite its benefits-is said to pose for a politically committed feminism. I begin with a brief recapping of the postmodernist challenge to the tenets of social science. I then advance a two-part argument promoting discourse analysis for feminist scholars who seek to benefit from postmodernism's respect for difference and inclusivity, yet refuse to give up a critical perspective. The first part of the argument deals with the charge that the postmodern turn disables critical inquiry; the second with the related debate over the need for `generalizing' or `totalizing' concepts (e.g. the concept `women') in the service of a feminist politics. I argue that postmodernist scholars' wide-spread tendency to discuss language outside its context of use has hobbled their ability to respond to this serious challenge, and I suggest that a closer look at routine talk can help feminists reframe these debates about politicality in helpful ways.
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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 | 0.109 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.011 | 0.076 |
| Scholarly communication | 0.021 | 0.036 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".