Psychopathy and Mental Imagery: The Role of Imagery in Social Dominance, Callousness, and Impulsivity
Bibliographic record
Abstract
An inability to see mental images may contribute to the development of psychopathic traits. This study examined the relationship between trait vividness of mental imagery, spontaneous use of imagery, and psychopathic traits in undergraduates ( N = 836, 80.6% female). Results did not support that psychopathy is associated with imagery deficits. Vividness positively predicted total psychopathy and Boldness, and spontaneous use of imagery negatively predicted Meanness. Mediations revealed less vivid imagery associated with more impulsivity and therefore increased psychopathic traits. Findings suggest the generation of vivid images fuels the socially dominant elements of psychopathy, whereas a lack of generating or using imagery facilitates callousness and limits opportunities for behavioral control. Findings support the use of imagery-based cognitive behavioral therapy interventions that target the disparities in the generation of vivid images that fuel maladaptive attitudes and behaviors, which be key in mitigating the instrumental and reactive behaviors seen in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".