Bibliographic record
Abstract
Mutilation is a rare and unusual act performed on a victim, especially in cases of homicide. Knowledge on mutilation homicide is scarce as the base rate of this type of homicide is very low. Moreover, previous studies examining this specific criminal behavior have been mainly descriptive, neglecting to look at other factors related to the act of mutilation. Furthermore, depending on the cultural context and country of origin, the infliction of mutilation pre-, per-, or post-homicide translates into different meanings. Therefore, it is important to examine mutilation homicide in the context of non-Western countries. Using crime and forensic examination reports subjected to forensic examination and convicted for a homicide between 1995 and 2011 ( N = 1,200) in Korea, the rate of mutilation homicide was estimated. Based on the 65 cases (5.4%) identified, information on the offenses and offenders were described. Moreover, using a series of bivariate analyses, the current study compared cases of mutilation homicides in Korea with other countries. Findings revealed interesting differences and similarities between mutilation homicide cases from Korea and the other countries. For instance, offender–victim relationship, victim’s gender, and criminal history were significantly different from the comparison groups. In addition, compared with Korea, mutilation homicide cases were significantly more likely to involve an accomplice in Finland, suggesting the need to carry the body over a long distance. Investigators and researchers need to understand the cultural context in which these acts are committed as the infliction of mutilation may serve different purposes across different countries.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".