Bibliographic record
Abstract
One problem highlighted by intersectional and Black feminist theory is that not all oppressed agents are oppressed in the same ways and to the same degree. One of the implications of this for responsibility practices is that social practices of exculpation will not apply equally across all agents. This article explores two false social narratives about far-right women and evaluates them according to the standard view of moral responsibility. The first narrative of misogyny as exculpation holds that far-right women are themselves victims of oppression (of the misogyny of their own movements) and thus not blameworthy for their actions, as misogyny undermines their control and knowledge on the standard view of moral responsibility. The second narrative of infantilization as exculpation also proposes that women lack both knowledge and control on the standard view. The narrative tells us that (White) women, unable to protect themselves, must be protected and avenged by (White) men. If we assume the standard view of moral responsibility, both of these narratives impede our ability to hold far-right women responsible. By instead proposing the adoption of the rational relations view of Angela Smith, this article seeks to demonstrate how a nonvolitionalist account of responsibility can itself become a feminist response to far-right women’s extremism with larger implications for our responsibility practices as a whole.
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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 | 0.006 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.135 | 0.114 |
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".