Pain, Power, and Policing: Emotional Injustice in Healthcare
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chronic pain patients frequently encounter not only physical suffering but also emotional dismissal and misrecognition in clinical settings. This paper argues that such experiences reflect a pervasive form of structural harm: emotional injustice. Chronic pain sufferers, especially women and members of marginalized groups, are often subject to emotion policing-the unjust regulation of emotional expression that distorts, suppresses, or discredits their feelings of frustration, sadness, and anger. Stereotypes like "women are emotional" or "boys don't cry" shape how patients' pain is interpreted and whether their emotional expressions are seen as credible, appropriate, or pathological. As a result, patients' emotions are routinely misread, their reports of pain discounted, and their treatment delayed or denied. Through the lens of emotion stereotyping, display suppression, and emotion hegemonizing, I show how dominant emotional norms constrain how chronic pain patients can express distress and advocate for themselves. These practices compromise emotional autonomy-their ability to experience and express fitting emotions in ways that reflect their circumstances, values, and lived reality-and reinforce systemic inequities in healthcare. While these harms intersect with forms of epistemic injustice, I argue that emotional injustice captures a distinct and deeper wrong: the denial of patients' ability to make sense of and communicate their emotional suffering on their own terms. Recognizing emotional injustice in the treatment of chronic pain is crucial for promoting more equitable, respectful, and compassionate care-care that honors the emotional realities of patients' lives.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| 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 it