CRIMINAL ACHIEVEMENT, OFFENDER NETWORKS AND THE BENEFITS OF LOW SELF‐CONTROL
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: Theoretical or conceptualConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.844
- Threshold uncertainty score
- 0.289
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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) | 0.000 | 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)
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
- 0.249 · 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 follows recent research on criminal earnings and examines the impact of underlying traits (low self‐control) and personal organization features (nonredundant networking) on the criminal earnings of a sample of incarcerated offenders previously involved in market and predatory crimes. Controlling for various background factors (age, noncriminal income, lambda and costs of doing crime), both low self‐control and nonredundant networking independently explain why some offenders are more successful than others in achieving higher monetary standards through crime. Although efficient, brokerage‐like networking enhances market offenders' earnings, low self‐control emerges as an asset for predatory offenders: the lower their self‐control, the higher their criminal earnings. For market offenders, however, low self‐control has no direct effect, but it does mitigate the impact of effective networking on criminal earnings. The results emerging from this study have implications for Gottfredson and Hirschi's theory of crime and the advent of a criminal network perspective. Extensions are also made toward the conventional/criminal embeddedness framework and deterrence research.
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
- Criminology
- Topic
- Crime Patterns and Interventions
- Field
- Social Sciences
- Canadian institutions
- Natural Sciences and Engineering Research Council of Canada
- Funders
- not available
- Keywords
- EarningsEmbeddednessControl (management)Perspective (graphical)Crime controlDeterrence (psychology)Sample (material)Deterrence theoryAsset (computer security)CriminologyBusinessPsychologyEconomicsCriminal justiceComputer securityPolitical scienceAccountingSociologyLawManagementComputer science
- Has abstract in OpenAlex
- yes