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Record 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 on OpenAlexaboutno aff
Kevin E. Davis

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2001
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationProperty (philosophy)EnforcementBusinessTerrorismFlow of fundsLaw and economicsLawConventionSubject (documents)Political scienceLaw enforcementPower (physics)Order (exchange)EconomicsFinance

Abstract

fetched live from 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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.345
Threshold uncertainty score0.685

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0050.013
Scholarly communication0.0200.009
Open science0.0010.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.045
GPT teacher head0.272
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2001
Admission routes1
Has abstractyes

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Same venueUniversity of Toronto Press eBooksSame topicCriminal Law and EvidenceFrench-language works237,207