Grey Zone Enablers:The impact of Canada's Pacific Rim strategy on the Vancouver model of money laundering
Bibliographic record
Abstract
This thesis explores the economic security and prosperity policy challenges that make British Columbia and Canada vulnerable to money laundering and illicit finance. It studies the influence of Canada's Pacific Rim strategy on provincial efforts to combat money laundering by examining the hearing transcripts from the Commission of Inquiry into Money Laundering. The first part uncovers latent factors and confounders that weaken BC's resilience against money laundering through thematic content analysis with unsupervised and semi-supervised topic models. The second part enhances the Walker-Unger economic gravity model by integrating cultural and ecological dimensions influenced by the Vancouver model of money laundering and the Pacific Rim strategy. It identifies vulnerabilities despite implemented countermeasures and investigates factors affecting the proportion of money laundering flow between Canada and China. This study demonstrates that socio-computational approaches with proxy variables enhance ethical intelligence-led policing strategy, especially when access to fair, accurate, and transparent data is limited.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".