Judging Inappropriateness in Actions Expressing Emotion: A Feminist Perspective
Bibliographic record
Abstract
Actions expressing strong emotions such as anger can be appropriate responses when an agent judges a serious injustice to have been committed. Certainly, a woman can experience these conditions and express herself through actions such as gesturing aggressively, gritting her teeth, or lashing out verbally. If she is consequently labeled “crazy,” “hysterical,” or “a bitch,” what has gone awry? This paper offers an analysis of the common charge of inappropriateness in the case of women’s actions expressing emotion. To begin, I will present core normative distinctions that define appropriate emotional expression. Following this, the “double-bind” of women’s actions expressing emotion will be explored with reference to the conflicting normative practices outlined in the first section of the paper. Put briefly, when a female agent surpasses gendered behavioral expectations, she is seen as having failed what can be called the first test of social coping. The perception of this failure shuts down further avenues for interpreting her behavior. Instead, the social inappropriateness of her emotion is used as further proof of irrationality. The arguments of the second section leave no doubt that gendered norms in the case of actions expressing emotions must be rejected both on epistemological and moral grounds. The final section of the paper explores epistemically and ethically viable alternatives for deciding the rational appropriateness of actions expressing emotion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".