Youth probation officers in British Columbia: the use of discretion and the effects of victimization decisions to breaching young offenders
Bibliographic record
Abstract
The majority of the current research on probation officers focuses on training methodology, job stress, arming for protection, and issues involved with identifying their role as a social worker or a police officer. What the current research lacks is an analysis of the decision making processes of probation officers and the factors that influence their decisions. Due to the mandates associated with the Youth Criminal Justice Act, Youth Probation Officers in Canada are heavily involved in the lives of those they monitor. With this increased level of involvement, new challenges exist for probation officers. The current study aimed to investigate the use of discretion in breaching by Youth Probation Officers and whether the use of discretionary decision making was impacted by a Youth Probation Officer being victimized by a probationer. To ascertain the decision making of youth probation officers, a self-administered, semi-structured survey was distributed to all youth probation officers in attendance at the Youth Justice Forum in Vancouver on February 7th and 8th, 2008.\n\nThis study found that while respondents indicated overwhelmingly (94.3 per cent) that breaching a youth on conditions would decrease their level of criminal offending; the level of breaching a youth who failed to comply with their order did not reflect that opinion. A majority of Youth Probation Officers justified this action by indicating use of discretion. Moreover, a majority of Youth Probation Officers indicated that they had been victimized by a client, but that being victimized did not affect their level of breaching. Still, the data suggested that those who were victimized by a client breached substantially more than those who had not been victimized. In addition, the number of times that a Youth Probation Officer was victimized correlated with an increase in breaches.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".