MétaCan
Menu
Back to cohort
Record W3138652700 · doi:10.21810/jicw.v4i2.3754

Exploring the Radicalization Pipeline on YouTube

2021· article· en· W3138652700 on OpenAlexaffvenueabout
Amanda Champion

Bibliographic record

VenueThe Journal of Intelligence Conflict and Warfare · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsCanadian Association for Health Services and Policy Research
Fundersnot available
KeywordsRadicalizationChampionPipeline (software)CriminologyOrder (exchange)Political scienceComputer securityMedia studiesComputer scienceSociologyTerrorismLawBusiness

Abstract

fetched live from OpenAlex

On September 16, 2021, Amanda Champion presented Exploring the Radicalization Pipeline on YouTube at the 2021 CASIS Vancouver Defence and Security Advisory Network Workshop. Champion discussed incel and misogynistic radicalization on YouTube in order to uncover and explore its effect on the broader network of extremist groups.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0060.002
Scholarly communication0.0060.013
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0280.005

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 head0.164
GPT teacher head0.350
Teacher spread0.186 · 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 designObservational
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

Citations3
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of Intelligence Conflict and WarfareSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207