Violence brokers and super-spreaders: how organised crime transformed the structure of Chicago violence during Prohibition
Bibliographic record
Abstract
The rise of organised crime changed Chicago violence structurally by creating networks of rivalries and conflicts wherein violence ricocheted. This study examines the organised crime violence network during Prohibition by analysing ‘violence brokers’ – individuals who committed multiple violence acts that linked separate violent events into a connected violence network. We analyse the two-mode violence network from the Capone Database, a relational database on early 1900s Chicago organised crime. Across 276 violent incidents attributed to organised crime were 334 suspected perpetrators of violence. We find that 20% of suspects were violence brokers, and nine brokers were violence super-spreaders linking the majority of suspects. We also find that violence brokers were in the thick of violence not just as suspects, but also as victims – violence brokers in this network experienced more victimisation than non-brokers. Unknowingly or knowingly, these violence brokers wove together a network, attack-by-attack, that transformed violence in Chicago.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".