Factor structure of the B-Scan 360: A measure of corporate psychopathy.
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
Psychopathy is a clinical construct defined by a cluster of personality traits and behaviors, including grandiosity, egocentricity, deceptiveness, shallow emotions, lack of empathy or remorse, irresponsibility, impulsivity, and a tendency to ignore or violate social norms. The majority of empirical research on psychopathy involves forensic populations most commonly assessed with the Psychopathy Checklist-Revised (PCL-R), a 20-item rating scale that measures 4 related factors or dimensions (Interpersonal, Affective, Lifestyle, and Antisocial) that underpin the superordinate construct of psychopathy. Recently, researchers have turned their attention to the nature and implications of psychopathic features in the workplace. This research has been hampered by the lack of an assessment tool geared to the corporate/organizational world. Here we describe the B-Scan 360, an instrument that uses ratings of others to measure psychopathic features in workplace settings. In this study, large samples of participants used an online survey system to rate their supervisors on the B-Scan 360. Exploratory and confirmatory factor analyses supported a reliable 20-item, 4-factor model that is consistent with the PCL-R 4-factor model of psychopathy. Although more research is needed before the B-Scan 360 can be used in organizational settings, we believe that these results represent an important step forward in the study of corporate psychopathy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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