Paths to Destruction: The Lives and Crimes of Two Serial Killers<sup>*</sup>
Bibliographic record
Abstract
Although research into the phenomenon of serial murder has revealed that serial killers frequently do not fit the initially described paradigm in terms of their physical and psychological profiles, backgrounds, and motives to kill, the media continues to sensationalize the figures of such killers and the investigators who attempt to analyze them on the basis of aspects of their crimes. Although the so-called "typical" profile of the serial murderer has proven accurate in some instances, in many other cases the demographics and behaviors of these killers have deviated widely from the generalized assumptions. This report details two unusual cases in which five and eight murders were committed in upstate New York. The lives and crimes of these offenders illustrate the wide spectrum of variations in the backgrounds, demographics, motivations, and actions witnessed among serial murderers, and highlight the limitations and dangers of profiling based on generalities.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".