COMMUNITIES, STREET GUNS AND HOMICIDE TRAJECTORIES IN CHICAGO, 1980–1995: MERGING METHODS FOR EXAMINING HOMICIDE TRENDS ACROSS SPACE AND TIME*
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
We merge Exploratory Spatial Data Analysis (ESDA) and a semi‐parametric, group‐based trajectory procedure (TRAJ) to classify communities in Chicago by violence trajectories across space. Total, street gun and other weapon homicide trajectories are identified across 831 census tracts between 1980 and 1995. We find evidence consistent with a weapon substitution effect in violent neighborhoods that are proximate to one another, a defensive diffusion effect of exclusively street gun‐specific homicide increases in neighborhoods bordering the most violent areas, and a spatial decay effect of temporal homicide trends in which the most violent areas are buffered from the least violent by places experiencing mid‐range levels of lethal violence over time. In merging these two methods of data analysis, we provide a more efficient way to describe both spatial and temporal trends and make significant advances in furthering applications of space‐time methodologies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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