Bibliographic record
Abstract
The article examines the recent individual level extensions to Institutional Anomie Theory. It explores if a marketized mentality is important to the development of a violent street code that encourages violence as a method of self-enhancement, as well as a factor directly leading to violence. Further, it investigates if the impact of the marketized mentality on violence is moderated by risk-taking and violent peers. It controls for other important factors associated with violence including physical abuse, homelessness, violent victimization, and social bonds. The research utilizes self-report data from interviews with 400 Canadian homeless youth aged 16-24. Results from the OLS regressions indicated that a marketized mentality, along with risk-taking, violent peers, violent victimization, and social bonds predicted levels of support for the street code. The marketized mentality had a direct effect on violence, as well as an indirect effect through the street code. The effect of marketized mentality on violence was also stronger at higher levels of risk-taking and violent peer association. Physical abuse, violent victimization, risk-taking, and violent peers also had direct effects on violence. The findings suggest that a marketized mentality can be adopted even in economically marginal populations leading to the development of violent strategies to fulfill goals. Avenues for future research are offered.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".