Anti-money Laundering and Counter-terrorist Financing Policy in Canada: Origins, Implementation, and Enforcement
Bibliographic record
Abstract
This thesis outlines and traces the process of reporting transactions that may be related to money laundering or terrorist financing in Canada. First, this dissertation examines the enactment of the Proceeds of Crime (Money Laundering) and Terrorist Financing Act (PCMLTFA). The process of legislating against these activities was one of norm recursivity, in which Canadian parliamentarians increasingly adopted the standards of the Financial Action Task Force--a group of the G8 mandated to standardize and harmonize national anti-money laundering legislation--not because of global hegemonic pressure, but because of an increasing awareness of Canada's own role as a global citizen in the international community. This work then examines the implementation of this legislation by looking at its deployment in Canadian retail banking. It examines at the process of training financial institution employees to engage with the PCMLTFA, and subsequently the use of the PCMLTFA by employees. This study argues that the risk management techniques in the bank responsibilize employees through responsibilization and normalization; however, the presentation of anti-money laundering and counter-terrorist financing (AML/CTF) legislation to employees may be problematic insofar as the stresses on adverse consequences to employees may be overstated, leading to over-reporting by employees in an effort to manage their own risks. Next, it looks at the ways bank employees are trained to use the legislation, how they understand their legal obligations, and how they use the legislation to identify transactions that appear suspicious or unusual. It demonstrates that bank employees are transformed into third party police, engaging in the detection of suspicious financial transactions on behalf of the government, and interrogates the implications of this development in the AML/CTF complex. This study also examines the detection of suspicious transactions by employees, and demonstrates that both factors directly related to the transaction, such as the amount of money and financial instrument presented, and factors related to the client, such as race, age, sex, and gender, can influence an employee's perception of the legitimacy of this transaction. It then concludes by identifying directions for future research and discussing the scholarly contributions of this study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".