Western Criminology Review 5(2), 97-107 (2004) Managing the Transition from Institution to Community: A Canadian Parole Officer Perspective on the Needs of Newly Released Federal Offenders
Bibliographic record
Abstract
The purpose of the study was to describe the needs of newly released federal offenders as perceived by community parole officers. Seventy-four parole officers were asked to answer the following question: “What do offenders need to succeed in the first 90 days after release? ” The data were analyzed using multidimensional scaling and cluster analysis. Seven clusters resulted. In the first cluster, food, clothing, and shelter were identified as well as health and transportation needs. In the second cluster, life skills including problem-solving, and budgeting skills were reported. The third cluster included education and employment assistance. In the fourth cluster, the need for correctional programs was identified. The fifth cluster described the need for offenders to have insight into their problem areas. In the sixth cluster, preparation for community supervision during incarceration was described. The seventh cluster described the need for structure of parole decreasing over time. The results are generally consistent with the available literature, indicating that parole officer assessment of offender needs following release into the community is based on factors that have been identified in previous research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".