Policing Complex Criminality in and through Major Seaports
Bibliographic record
Abstract
This chapter provides a framework for analysing large-scale, organised and complex criminality through and within major seaports and the challenges of policing these activities. The chapter’s main aim is to analyse how organised crime, organisational crime and forms of collusion and/or corruption on the waterfront and in/through seaports should be understood as complex crimes, in as much as they involve different types of activities, more or less serious or harmful in nature and more or less local in reach. Drawing on data collected in the ports of Genova, New York/New Jersey, Montreal, Melbourne, Liverpool and Gioia Tauro in particular, the chapter reflects on practical challenges and the practices of policing the port space. In doing so, the chapter establishes that the policing of complex crimes on the waterfront and in/through seaports is a form of hybrid policing, between high and low control mechanisms. It concludes with an analysis of the consequences this has for local partnerships and long-lasting interventions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".