Differential Cost Avoidance and Successful Criminal Careers
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
Using a sample of adjudicated French Canadian males from the Montreal Two Samples Longitudinal Study, this article investigates individual and social characteristics associated with differential cost avoidance. The main objective of this study is to determine whether such traits are randomly distributed across differential degrees of cost avoidance or whether they reflect some degree of rationality. Differential cost avoidance is a composite measure that includes the ratio of self-reported career length to officially recorded career length, the ratio of self-reported offending gravity to officially recorded gravity, and the ratio of time “free” to periods of incarceration. Findings reveal that it is particularly difficult to predict differential cost avoidance at early ages. The main predictors of the residual degree of differential cost avoidance in the early 30s include substance use (especially drugs), the accumulation of debts, and the use of violence in the perpetration of crime. Implications for desistance research are discussed.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it