Perceptual biases in facial emotion recognition in borderline personality disorder.
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
Individuals with borderline personality disorder (BPD) have biases in facial emotion recognition, which may underlie many of the core features of this disorder. Although they are known to misperceive specific prototypic expressions of emotion (i.e., those displayed at full emotional intensity), patients with this disorder may also show biases in their perceptions of emotions that are expressed at lower levels of emotional intensity. Females with BPD (n = 31) and IQ- and demographically matched nonpsychiatric controls (n = 28) completed a task assessing the recognition of neutral as well as happy and sad facial expressions at mild, moderate, and prototypic emotional intensities. Whereas patients with BPD were more likely than controls to ascribe an emotion to a neutral facial expression, they did not consistently attribute a more negative or positive valence to these faces as compared with controls. Patients were also more likely to perceive mildly sad facial expressions as more intensely sad, and this finding could not be attributed to depressed mood. The results of this study suggest that perceptions of even subtle expressions of negative affect in faces may be subjectively magnified by individuals with BPD, although there was no consistent evidence for a negative perceptual bias for faces displaying a neutral expression. These biases in facial emotion perception for patients with BPD may contribute to difficulties understanding others' emotional states and to problems engaging effectively in social interactions.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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