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Record W1580445022

North American Foreign Fighters

2014· article· en· W1580445022 on OpenAlexaboutno aff
Michael Noonan, Phyl Khalil

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsWritPolitical scienceState (computer science)PhenomenonForeign policyIslamPolitical economyInternational securityLawDevelopment economicsCriminologySociologyPoliticsHistoryEconomics
DOInot available

Abstract

fetched live from OpenAlex

While the phenomenon of so-called “foreign fighters” is in no way new the past thirty-plus years has shown a marked increase in the numbers of individuals traveling abroad to fight in civil conflicts in the Muslim world. The crisis in Syria (2011-present) has created a massive influx of such individuals going to fight. Of particular concern in western capitals has been the numbers of individuals from those countries that have gone to fight in that conflict which has since crossed the border into neighboring Iraq with the establishment of the socalled “Islamic State” and threatens to broaden the conflict into a larger regional sectarian conflagration. While the numbers of such participants from Western Europe have been greater than those who have gone from the United States and Canada there are legitimate concerns in both Washington, DC, and Ottawa about American and Canadian citizens who have gone—or attempted to go—to fight there and in other locales such as the Maghreb and Somalia. The analysis here will provide some background on the foreign fighter phenomenon, discuss the foreign fighter flow model, explore the issue from both Canadian and US perspectives to include providing details of some original research categorizing the characteristics of a small sample of US and Canadian fighters and those who attempted to go and fight, discuss how both governments have attempted to deal with the issue, and offer some policy prescription for dealing with this issue that is of importance to both international security writ large and domestic security in the US and Canada.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.702
Threshold uncertainty score0.599

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0510.008

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 head0.199
GPT teacher head0.557
Teacher spread0.357 · 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 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
Published2014
Admission routes1
Has abstractyes

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