Bibliographic record
Abstract
Psychopaths. Who are they? What are they? How do they differ from the rest of us "normals?" And, why do they differ from the rest of us "normals?" For most of us, the word "psychopath" conjures up images of notorious serial killers, like Charles Manson, Ted Bundy, Jeffrey Dahmer, or Hannibal Lecter. However, psychopaths are not necessarily just serial killers. There crimes are often, and typically, petty offences, social misdeeds, or "crimes of the heart." They can be found in every community and in every profession. For the most part, they are identified in the psychological literature in terms of having an emotional deficit. Their characteristic feature, along these lines, is a lack of empathy, which is an imperative source of moral motivation. As such, philosophers generally discuss psychopaths in the context of notions associated with freedom and moral responsibility. The main question that is typically examined by philosophers, in this context, is whether or not psychopaths can legitimately be held morally responsible for their actions in light of their inherent lack of empathy. However, philosophers rarely make close contact with the psychological literature to examine the nature of the psychopath in developing their views. In this project, I briefly examine and explicate the psychological literature that illuminates the nature and development of the psychopath - from both the nature and nurture perspectives. By doing so, I am able to lay a foundation upon which a critical comparison can be made - between the nature of the psychopath and the nature of the non-psychopath - in working towards determining the essential ingredients that constitute moral agency, subsequent attributions of moral responsibility, and, ultimately, whether or not psychopaths can legitimately be held morally responsible for their actions.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| 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".