Grievance-fueled sexual violence
Bibliographic record
Abstract
The grievance fueled violence paradigm encompasses various forms of targeted violence but has not yet been extended to the theoretical discussion of sexual violence. In this article, we argue that a wide range of sexual offenses can be usefully conceptualized as forms of grievance fueled violence. Indeed, our assertion that sexual violence is often grievance fueled is unoriginal. More than 40 years of sexual offending research has discussed the pseudosexual nature of much sexual offending, and themes of anger, power, and control - themes that draw clear parallels to the grievance fueled violence paradigm. Therefore, we consider the opportunities for theoretical and practical advancement through the merging of ideas and concepts from the two fields. We examine the scope of grievance in the context of understanding sexual violence, and we look to the role of grievance in the trajectory toward both sexual and nonsexual violence, as well as factors that might distinguish grievance fueled sexual from nonsexual violence. Finally, we discuss future research directions and make recommendations for clinical practice. Specifically, we suggest that grievance represents a promising treatment target where risk is identified for both sexual and nonsexual violence.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".