Transnational evaluation of the Sympathy for Violent Radicalization Scale: Measuring population attitudes toward violent radicalization in two countries
Bibliographic record
Abstract
Countering violent radicalization is a priority in many countries, prompting research that assesses attitudes and beliefs about violent radicalization in the general population. The majority of violent radicalization assessments have been developed among specific populations, with limited investigation into the generalizability and cross-cultural applicability of measurement tools. A transcultural investigation raises questions about the implicit assumptions and norms that inform instrument development. This research examined the psychometric properties of the Sympathy for Violent Radicalization Scale (SyfoR), a measure developed for use with Pakistani and Bangladeshi immigrant groups in the UK, in two convenience samples of youth and young adults in North America and Western Europe. We investigated the factor structure, reliability, and construct validity of adapted versions of the SyfoR among convenience samples of youth and young adults living in Belgium ( N = 2014) and in Quebec, Canada ( N = 1364) via online surveys administered to students engaged in secondary and post-secondary education. Results indicate that, in both samples, a reduced, 8-item version of the SyfoR has a 3-factor structure with good model fit statistics using confirmatory factor analysis and good internal consistency reliability. More studies are needed to assess the appropriateness of the SyfoR for use in diverse contexts and among diverse populations. The potential usefulness and harmfulness of measures of violent radicalization should balance the benefits of obtaining local data with the risks associated with pathologizing social dissent.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".