Bibliographic record
Abstract
In this paper, I argue that the social norms that underlie our emotion regulation practices can result in further oppression of girls and women under conditions of patriarchy. One aspect of this oppression is the disproportionate responsibility for emotions that is taken on by girls and women in the wake of emotional distress caused by misogynistic aggression. I show that although emotion-regulation techniques are understood as ideal tools for enhancing agency and subjective well-being, and emotional labor is not necessarily oppressive, they may not only enable a perpetrator’s ability to evade accountability but also, by outsourcing emotional regulation, allow the perpetrator to fail to cultivate emotional intelligence, which leads to a vicious cycle. In these cases, girls and women also face a double bind. If certain emotion-regulation practices succeed in aligning emotions with dominant social norms, we face emotional labor that not only benefits the regulator but feeds the cycle described above, and we face alienation from our apt feelings. If we fail to regulate our emotions by accepted standards and patriarchal entitlements, we may be outcast, pathologized, or otherwise marginalized. I argue that the consequences of this double bind constitute a site of affective injustice and expose asymmetrical relations of moral accountability in evaluations of the fittingness of emotions.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".