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Record W3206171939 · doi:10.1177/13634615211047438

Evaluation of a training program on the prevention of violent radicalization for health and education professionals

2021· article· en· W3206171939 on OpenAlexaffabout
Élise Bourgeois-Guérin, Diana Miconi, Aude Rousseau-Rizzi, Cécile Rousseau

Bibliographic record

VenueTranscultural Psychiatry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsMcGill UniversityUniversité de MontréalUniversité TÉLUQ
Fundersnot available
KeywordsRadicalizationWorryPsychologyMedical educationModalitiesApplied psychologySocial psychologyTerrorismMedicinePsychiatryPolitical scienceSociology

Abstract

fetched live from OpenAlex

This article presents a preliminary evaluation of training sessions promoting a systemic approach to violent radicalization (VR) offered to first-line health and education professionals in Quebec. We describe the rationale and content for the training program, its general principles and implementation modalities. The mixed-method evaluation indicated that the participants felt the training increased their level of confidence in dealing with VR in their work. It appeared that training also shifted participants' attitudes significantly on four items with decreases: (1) worry about the extent of VR of young people in Quebec; (2) belief that VR should automatically be reported to the police; (3) thinking that Islam favors VR; and (4) assumption that enhanced security measures would have a deterrent effect on VR. The conclusion discusses the challenges associated with violent radicalization training programs, emphasizing the delicate ethical and political questions related to the provision of training on this socially divisive topic.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.109
GPT teacher head0.468
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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