Facilitating Group Discussion in Prison: Decolonizing, Destigmatizing and Egalitarian Approaches
Bibliographic record
Abstract
Drawing on literature from the fi elds of group dynamics and confl ict resolution, this article provides direction and guidelines for prison group facilitators.We start by describing the institutional prison context, the multiple forms of violence in the Canadian prison system and the trauma of those who occupy it.Next, we examine the ways that groups are facilitated in the prison system, contrasting the colonial and cultural safety approaches, and highlighting our experiences in circle with the Walls to Bridges program.We explore the role of social identity in groups and consider mechanisms to build group cohesion.Ultimately, we off er potential facilitators tools and knowledge so that together we can work toward healing and transformation.
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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 | 0.071 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.030 | 0.048 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.006 | 0.032 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".