Working With a Psychopath: Is There Light at the End of the Tunnel?
Bibliographic record
Abstract
Having a supervisor with psychopathic characteristics is related to being bullied, poorer job satisfaction, work/family life conflict, financial instability, and distress. To date, all research on corporate psychopathy victims considers how they are negatively impacted rather than potential positive outcomes. In response, this study examined how working with a psychopath impacts posttraumatic growth (PTG). Utilizing a mixed-methods approach, this study draws upon the experiences of 285 individuals who have worked with a colleague or supervisor with alleged psychopathic characteristics. Results indicated that approach coping and psychopathic characteristics predicted PTG. Qualitative analyses revealed that the majority of participants used various coping strategies (e.g., emotion-focused), received support (e.g., emotional), and underwent post-experiential growth or learning (e.g., positive personal growth); not all growth/learning was positive, however (e.g., less trusting). Results suggest that cultivating approach-focused coping strategies may enhance PTG following a traumatic event.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".