Emotional Reactivity to Social Rejection and Negative Evaluation Among Persons With Borderline Personality Features
Bibliographic record
Abstract
The present study examined the emotional reactivity of persons with heightened borderline personality (BP) features to social rejection and negative evaluation in the laboratory. Individuals with high levels of BP features (n = 30) and controls with low levels of BP features (n = 44) were randomly assigned to a condition involving negative evaluation based on writing (negative evaluation/academic), or a condition involving negative evaluation based on personal characteristics as well as social rejection (negative evaluation/social rejection). Hypothesis 1 was that high-BP individuals, but not low-BP controls, would show greater emotional reactivity to the negative evaluation/social rejection stressor, compared with the negative evaluation/academic (writing) stressor. Hypothesis 2 was that high-BP individuals would specifically show greater reactivity of shame- and anger-related emotions to the negative evaluation/social rejection stressor compared with the negative evaluation/academic stressor. Findings indicated that high-BP individuals showed heightened emotional reactivity to the social rejection stressor but not to the negative evaluation stressor, but the opposite pattern occurred for controls. In addition, there was evidence for heightened reactivity of irritability, distress, and shame for the high-BP group, specifically in the social rejection condition.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".