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Record W2086589546 · doi:10.1080/14781150903487956

Homegrown terrorism and transformative learning: an interdisciplinary approach to understanding radicalization

2010· article· en· W2086589546 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Change Peace & Security · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRadicalizationTransformative learningTerrorismSociologyPolitical scienceCriminologyPsychologyEpistemologySocial psychologyPolitical economyEnvironmental ethicsLawPedagogyPhilosophy

Abstract

fetched live from OpenAlex

Since 2001, a preponderance of terrorist activity in Europe, North America, and Australia, has involved radicalized Westerners inspired by al Qaeda. Described as ‘homegrown terrorism’, perpetrators are citizens and residents born, raised, and educated within the countries they attack. While most scholars and policy-makers agree that radicalization plays a central role in persuading Westerners to embrace terrorism, little research properly investigates the internal and cognitive processes inherent to radicalization. Transformative learning theory, developed from the sciences in education, health, and rehabilitation, provides an unconventional and interdisciplinary way to understand the radicalization process. The theory suggests that sustained behavioural change can occur when critical reflection and the development of novel personal belief systems are provoked by specific triggering factors. In applying transformative learning theory to homegrown terrorism, this study helps explain how formerly non-violent individuals come to condone, legitimize, and participate in violent behaviour.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.365
Teacher spread0.283 · 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