Preventing Violent Extremism through Mentoring? Outcomes and Insights from a Quebec-Based Program
Bibliographic record
Abstract
Although research on the tertiary prevention of violent extremism has increased over the past decade, clear benchmarks for best practices remain scarce. Existing studies often suffer from methodological and ethical limitations and seldom incorporate the perspectives of those most directly affected—namely, the individuals targeted by these programs. Nevertheless, a growing body of literature highlights the promise of social rehabilitation approaches, such as mentoring programs. This article examines a mentoring program developed by a Quebec-based clinical team specializing in the prevention of extremism and violent radicalization. It explores the program’s impact from the perspectives of mentees, mentors, and clinicians. Based on a qualitative analysis of 15 individual semi-structured interviews and 2 focus groups, the study identifies the program’s strengths and limitations. Overall, participants viewed the mentoring program positively. Among the positive effects was the creation of a secure relational space that enabled some mentees to break out of isolation through meaningful interpersonal engagement. However, the mentoring relationship also presented challenges, including the potential for mentees to reproduce or reinforce past negative relational experiences. Robust clinical support is therefore essential to mitigate these risks and to safeguard the well-being of both mentees and mentors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".