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Record W3197517621 · doi:10.5038/1944-0472.14.3.1934

The Validity of the Assessment and Treatment of Radicalization Scale: A Psychometric Instrument for Measuring Severity of Extremist Muslim Beliefs

2021· article· en· W3197517621 on OpenAlexaffabout
Y Karimi, Adarsh Kholi, Anni Hesselink, Johan Prinsloo, Stella Bhawanie, José Manuel Andreu Rodríguez, Adekunle G. Ahmed, Wagdy Loza

Bibliographic record

VenueJournal of Strategic Security · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsQueen's UniversityCentre for Addiction and Mental Health
Fundersnot available
KeywordsRadicalizationScale (ratio)Reliability (semiconductor)PsychologyTerrorismDiversity (politics)Political scienceSocial psychologyGeographyLaw

Abstract

fetched live from OpenAlex

The Assessment and Treatment of Radicalization Scale (ATRS) is designed to quantitatively measure Muslim extremists’ ideologies regarding risk areas that are reported in the literature. Utilizing the scale, in this study, using a convenience sample of 1769 from 10 countries (Australia, Canada, Egypt, India, Iran, Iraq, Nigeria, Pakistan, Spain, and South Africa) responded to the ATRS. Results supported previous findings about the reliability and validity of the Assessment and Treatment of Radicalization Scale (ATRS, formerly known as Belief Diversity Scale BDS, Loza, 2007) for assessing Muslim extremists. Suggested cut off scores to use for identifying possible extremists are provided.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.125
GPT teacher head0.363
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2021
Admission routes2
Has abstractyes

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