All Walks of Life: Editorial for the Special Issue on “The Impact of Psychopathy: Multidisciplinary and Applied Perspectives”
Bibliographic record
Abstract
We are grateful for the opportunity to serve as Guest Editors of this Special Issue on "The impact of psychopathy: Multidisciplinary and applied perspectives." Psychopathy is a serious public health concern that has long attracted scholarly and clinical interest in both mental health and criminal justice fields. However, given its robust link with criminal behavior, research on psychopathy has largely developed with a primary emphasis on (male) adults within correctional settings. While the preponderance of work remains focused on these adult offenders, research on psychopathy has expanded in recent decades to include studies within a variety of more diverse populations and contexts. The goal of this Special Issue has been to highlight some of the most recent research in these areas, toward a more deliberate emphasis on the broad impacts that psychopathy can impart across all walks of life. To this end, while only two of the papers included in the Special Issue focused on forensic samples (and more specifically on treatment and recidivism), all 10 papers have nonetheless offered a clear focus on the detrimental impacts that individuals with psychopathic traits can impart within society. Indeed, included manuscripts focused on the impact of psychopathy within romantic relationships (in both middle and older adulthood), within parent-child dyads, within the workplace, and within society at large. Across these studies, the significant, detrimental impact that individuals with heightened psychopathic traits impart is highlighted, not only for their victims, but also for their family, friends, and colleagues. In this Editorial, we would like to emphasize some main themes that emerged from their contributions.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".