Computational Analysis of Personality and Emotion in Semi-Structured Interviews
Bibliographic record
Abstract
Psychopathy is a personality disorder involving deficits in affective characteristics and behaviour (Cleckley, 1988;Hare, 2003).Previous studies have found relationships between psychopathy and negative polarity in text, as well as psychopathy and specific semantic content (e.g., Body, Family) (Garcia & Sikström, 2014;Hancock, Woodworth, & Porter, 2013;Sumner, Byers, Boochever, & Park, 2012).The majority of these studies were performed with non-clinical psychopathy (from the general population), and the only study on clinical psychopathy (from institutionalized populations) failed to find support for a relationship between overall psychopathy and negative polarity (Hancock et al., 2013).The current study explores emotion and semantic categories in further detail with both a non-clinical and a clinical sample.Findings were inconsistent with the majority of previous research, suggesting that linguistic correlates of psychopathy are variable.The prevalence of such correlates is possibly dependent on sample size and text source.Discussion…..…..
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".