Differentiating between Physically Violent and Nonviolent Stalkers: An Examination of Canadian Cases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study is one of a few that empirically investigated factors that differentiated the physically violent stalker from the nonviolent stalker. Using discriminant analysis, 103 Canadian cases of "simple obsessional" stalking were examined. Overall, the success of the model for classifying cases into one of two groups was 81%. Results revealed that the physically violent stalker is more likely to: (a) have a stronger previous emotional attachment toward their victim; (b) be more highly fixated/obsessed with their victim; (c) have a higher degree of perceived negative affect towards their victim; (d) engage in more verbal threats toward the victim; and (e) have a history of battering/domestic abuse towards the victim. Overall, the variables that best differentiate the physically violent stalker from the nonviolent one appear to characterize underlying themes of anger, vengeance, emotional arousal, humiliation, projection of blame, and insecure attachment pathology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it