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Enregistrement W2297412333 · doi:10.3138/9781442682337-020

Cutting off the Flow of Funds to Terrorists: Whose Funds? Which Funds? Who Decides?

2001· book-chapter· en· W2297412333 sur OpenAlexaboutno aff
Kevin E. Davis

Notice bibliographique

RevueUniversity of Toronto Press eBooks · 2001
Typebook-chapter
Langueen
DomaineSocial Sciences
ThématiqueCriminal Law and Evidence
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLegislationProperty (philosophy)EnforcementBusinessTerrorismFlow of fundsLaw and economicsLawConventionSubject (documents)Political scienceLaw enforcementPower (physics)Order (exchange)EconomicsFinance

Résumé

récupéré en direct d'OpenAlex

One of the most important fronts in the newly declared war on terrorism is the financial one. The avowed aim of the United States and its allies is to cut off the flow of funds to terrorists. This campaign involves a two-pronged attack: The first prong involves prosecuting the financiers, i.e. individuals or organizations that provide money or property to support terrorist activities. The second prong involves freezing, seizing and forfeiting property that has been or might be directed toward terrorist activities. This paper analyses the portions of the Anti-terrorism Act that represent the federal government of Canada's first sortie on the financial front of the war against terrorism. Although the government's two-pronged strategy is simple to describe, it is actually inherently difficult to implement through legislation. One reason is because legislation of this sort is designed to capture economic activity that only poses a risk of contributing to future terrorist activity. This forces lawmakers to decide how much risk must be posed by a given activity before it ought to be criminalized, recognizing that the lower the threshold they establish, the more likely it is that they will capture activity that would not, if events proceeded in due course, actually lead to harm. A second challenge associated with legislation of this sort is to determine how close the connection between economic activity and terrorist activity must be in order for the economic activity to warrant criminal sanction. At some point the connection may be so remote that many reasonable people would conclude—for example, on the basis of concerns about personal liberty—that the economic activity should not attract criminal liability. My primary objective in this paper is a relatively modest one: I simply intend to describe how the drafters of the Anti-Terrorism Act have responded to the challenge of defining the relationship that must exist between individuals and property on the one hand, and terrorist activity on the other hand, in terms of both certainty and proximity, in order to trigger criminal penalties. Where appropriate I compare the approach taken in the new legislation to the approach that Canadian law has previously taken to similar issues, as well as to the approach adopted in the International Convention for the Suppression of the Financing of Terrorism (the 'Financing of Terrorism Convention'), which Canada signed on February 10, 2000. I do not attempt to assess directly whether the approach that the Anti-terrorism Act has taken is justifiable, since answering that question would involve canvassing a wide range of ethical, economic and political factors. However, towards the end of the paper, I do analyze the legislation in terms of the amount of power Parliament has given law enforcement officials, trial judges, juries and appellate courts respectively to determine which conduct should attract criminal sanction. I argue that some of the new provisions give law enforcement officials too much power and appellate courts too little.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,924
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0020,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,045
Tête enseignante GPT0,272
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2001
Routes d'admission1
Résumé présentoui

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