Understanding Youth Justice Professionals’ Motivations For Their Work
Bibliographic record
Abstract
Youth Justice (YJ) professionals experience work-related stress, challenges and trauma in their work (Sibisi & Warria, 2020) yet they continue to enter the field. Research regarding motivations of YJ professionals for their work is limited, but necessary to improve overall quality of care and to ensure the most suitable candidates are hired. Semi-structured interviews aimed to explore YJ workers’ motivations for their work and how they experience and cope with challenges on the job. Thematic analyses indicates that YJ professionals are motivated by the opportunity to contribute to the lives of youth through prevention and intervention, progress and learning, and advocacy and resource provision. Challenges in YJ work are often related to feeling unsupported owing to low salaries, staff shortages, and system constraints. Motivating factors which contribute to their ability to stay in the field despite the challenges include a passion for their work and seeing change in their clients. Healthy coping strategies appear necessary to manage challenges and may contribute to the longevity in the field. Findings provide insight into YJ professionals' motivations, coping, and reasons for remaining in the field. These results can help to inform hiring, training and policy in Ontario YJ work.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".