Validation of a multifactorial model of sexual sadism
Bibliographic record
Abstract
Longpré, Guay & Knight (2018) developed a multi-trajectory model of childhood, adolescence and adulthood problems and lifestyles in sadistic sexual aggressors. They identified three paths leading to sexual sadism: the schizoid, the disinhibition and the narcissistic-meanness paths. Although these paths share common ground in early childhood, nevertheless they diverge later on in life. The aim of the current study is to replicate and extent their study with a sample Canadian sexual aggressor of woman. In fact, in our analysis, we included additional variables as to the sexual and the general lifestyle of the offenders. The total sample consisted of 180 extra-familial sexual aggressors of woman (at least over sixteen years old). Among the offenders, 59 killed their victims. On the basis of latent class analysis, we identified two developmental paths. The first one, the schizoid avoidant path, is characterized by severe sexual and physical victimization in childhood and also social isolation, low self-esteem and sexual sadistic fantasies in adulthood. The second, the antisocial path is also characterized by severe victimization in childhood, but also polymorphic criminal behaviours as well as sensation seeking activities and a festive lifestyle in adolescence and adulthood. These two path share similarities with the results of Longpré et al. (2018). More specifically, our avoidant schizoid path largely corresponded to their schizoid path and the antisocial path shared several features with both the disinhibition and narcissistic path. The theoretical implications of those results as to the development of a model of sexual sadism will be presented.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".