Assessing Vulnerable and Strategic Positions in a Criminal Network
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: QualitativeConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.640
- Threshold uncertainty score
- 0.582
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.278 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
This study focuses on individual positioning within an illegal drug distribution network surrounding a reputed criminal organization (the Quebec Hells Angels). The aim is to distinguish between participants who were positioned vulnerably and/or strategically during a period when the network was targeted by an intensive law-enforcement investigation. Two centrality measures are used throughout the analysis. Degree centrality accounts for the number of direct contacts surrounding a participant. Betweenness centrality accounts for a participant’s brokerage leverage by measuring the scope of indirect relationships that s/he mediates. The final results reveal how differential positions in the network influence the judicial outcomes (arrests) within the case. Participants with high degree centrality were more likely to be arrested. Participants with high betweenness centrality were less likely to be arrested. Most importantly for law-enforcement concerns, those participants with high brokerage level were less likely to be members of the Hells Angels, thus suggesting that targeting strategies must take consider the patterns that represent an offender’s network at any given time, rather than simply focusing on an offender’s status and reputation within a criminal organization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Journal of Contemporary Criminal Justice
- Topic
- Crime, Illicit Activities, and Governance
- Field
- Social Sciences
- Canadian institutions
- Université de Montréal
- Funders
- not available
- Keywords
- Betweenness centralityCentralityLaw enforcementReputationLeverage (statistics)CriminologyEnforcementScope (computer science)Computer securityBusinessPolitical scienceLawPsychologyComputer scienceArtificial intelligence
- Has abstract in OpenAlex
- yes