Personality and life events in a personality disorder sample.
Bibliographic record
Abstract
Individuals with a personality disorder (PD) tend to experience more negative life events (NLEs) than positive life events (PLEs). In community samples, the Five Factor Model of personality (FFM) predicts both positive and negative life events. The present research examined whether FFM normal personality traits were associated with positive and negative life events among individuals with 1 of 4 PDs: avoidant, borderline, schizotypal, and obsessive-compulsive, and tested whether associations between the FFM of personality and PLEs and NLEs were similar across the 4 PD groups and a control group. Among aggregated PDs, neuroticism was positively associated with NLEs, whereas extraversion, openness to experience, and conscientiousness were positively associated with PLEs. Comparisons of each PD group to a control group of individuals with a major depressive disorder indicated that the FFM traits operated similarly across clinical samples with and without PD. Our findings indicate that normal personality traits can be used to help understand the lives of individuals with PD. (PsycINFO Database Record
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".