Gender, Trauma, and the Use of Trauma, Diversity and Inclusivity Principles During Probation and Parole Supervision
Bibliographic record
Abstract
Martinson (1974) argued that Nothing Works in the rehabilitation of justice impacted individuals. In response, Andrews and Kiesling (1980) developed a set of core correctional practices (CCPs) that could be used by probation and parole officers to enhance correctional outcomes for justice impacted individuals. More recently, trauma responsive approaches have emerged as another hypothesized effective strategy for dealing with justice impacted individuals who experience high levels of trauma (Miller & Najavits, 2012). This study investigates the nature and prevalence of probable traumatic experiences among justice impacted individuals on probation with a focus on gender differences (N ≈ 329). The study also investigates if probation and parole officers who were recently trained in a model of community supervision that blends trauma responsiveness with core correctional practices—the Ontario Ministry of the Solicitor General’s Made-in-Ontario Core Correctional Practices (CCP) Model of Community Supervision- are more likely to apply trauma, diversity and inclusivity (TDI) principles in their interactions with clients after the training. The study uses client case notes prepared by probation and parole officers. Results showed that despite women reporting significantly higher probable trauma, trauma-informed approaches were applied similarly across gender groups. In addition, TDI implementation was consistent regardless of trauma status in the context of CCP. This highlights the need for more targeted trauma-informed approaches based on individual needs rather than a generalized application of trauma-informed intervention. The opinions and views expressed in this report reflect those of the author and not the Ontario Ministry of the Solicitor General. Sohaila Abdelhadi contributed intellectually to the research, prepared the poster from their thesis work, and managed its submission. All authors contributed to data collection and coding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".