Today’s Offender, Tomorrow’s Victim: Analyzing the Connections Between Offenders and Victims
Bibliographic record
Abstract
This presentation examines the link between victims and offenders and how these roles are often interchangeable when it comes to a youth’s involvement in crime. Usually, this connection is disregarded because of the focus on the immediate situation and not the youth’s experiences with both roles. Because of this strong association between offenders and victims, the focus of this paper is about what stops a victim from becoming an offender and vice versa. The aspects focused on are individual and social factors, as well as the interactions and overlap between these factors. Generally, it was found that the criminal justice system and social service supports tend to only focus on individual factors while ignoring the social environmental aspects. This presentation demonstrates the importance of not only acknowledging a youth's role as both an offender and victim, but also the importance of addressing all aspects around how and why they got involved in criminal activity. By understanding the significance of these factors, this information can be used and integrated into the criminal justice system to help youth reduce their involvement in crime or to provide supports that address the cycle of victimization and offending. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled) Faculty Mentor: Michael Gulayets Department: Sociology
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".