Traveling to Violence: The Case for a Mobility-Based Spatial Typology of Homicide
Bibliographic record
Abstract
According to routine activities theory, crime is the result of an intersection between victims and offenders in both time and space. We introduce a spatial typology that identifies five combinations of victim and offender mobility to homicide incident locations: internal, predatory, intrusion, offense mobility, and total mobility types. The authors’ argue that the joint mobility pattern of the victim and offender is the mechanism underlying routine activities theory, and made explicit by the spatial typology. Using information on the 420 homicides in Pittsburgh, Pennsylvania, between 1987 and 1995, we demonstrate that the majority of homicides involve at least some mobility on the part of victims and/or offenders. Our results also indicate that mobility to homicide incident locations is most associated with event characteristics such as motive, rather than with characteristics of the participants. With most offenders committing the homicide outside of their own neighborhood, levels of lethal violence in a community are influenced more by the interaction among nonlocal participants than by the violent actions of local residents.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".