Organized crime, money laundering, and the real estate market in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines how the financial proceeds of organized criminal activity are laundered through the Canadian real estate market. The source of data for this study was cases from the Royal Canadian Mounted Police. Real estate has many attributes that make it an attractive destination for criminal proceeds. It provides a home in which the offender can live and is often used for the cultivation of marijuana. As a money laundering vehicle, a host of mechanisms commonly used with real estate transactions can frustrate efforts to unearth the criminal source of funds, such as nominees, fake mortgages, solicitor--client privilege, and legal trust accounts. There is some potential that money laundering through real estate can distort fair market values by contributing to inflated real estate prices, but this is unlikely given the fact that the volume of criminal proceeds invested in the real estate market is just a tiny fraction of overall investments and transactions on an annual basis.
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.
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 | 0.005 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it