“It’s all about the Money”: Crime in the Caribbean and Its Impact on Canada
Bibliographic record
Abstract
For most Canadians, the Caribbean is a place to take an idyllic break from winter. Sandy beaches and warm temperatures lure Canadians to the islands. Interaction with the local population is mostly limited to those who work in hotels and bars. What actually happens in the local communities is generally lost on the average Canadian. Appreciating the large Caribbean diaspora in Toronto and Montreal, the connections are dynamic between those sun-baked Caribbean communities and Canadian society. While those linkages are generally positive, there are disturbing trends in crime in the Caribbean. Herculean efforts are being made by the World Bank, the United Nations, and the regional Caribbean Development Bank to build regional capacity in governance and criminal justice systems. There is, however, a lack of political will by some Caribbean leaders to implement recommendations that would greatly improve citizen security and national institutions. Scholarly and professional studies have made recommendations for the security sector that are achievable, but the political will in many countries has been lagging. The Caribbean drug trade has long held the spotlight, but money laundering is increasingly a concern, especially with evidence of linkages between terrorist groups resident in Central America and Venezuela, which have close proximity to the Caribbean Windward Islands. Post-9/11 financial tools, utilized under the U.S. Patriot Act, have been effective in dealing with rogue governments, corrupt officials, and transnational criminal gangs. However, the use of the Internet for financial transactions and the emergence of digital currencies have made regulatory control challenging. This is significant considering the Canadian tourism, banking, and resource development in the region that have caused steady flows of Canadians, money and expertise to the Caribbean. This paper reviews Caribbean crime and its trends and impacts on Canada, money-laundering trends, and highlights policies that could be reinforced to better curb these trends. Crime is a societal problem for which solutions are found within communities. This applies equally to the Caribbean and to Canada. It is in Canada’s best interest to accelerate efforts to aid the region, especially in the area of citizen security and reforms of the criminal justice system. Multi-lateral programs aimed at building regional capacities in governance and criminal justice systems are the areas in which Canada can play an important role. The creation of a Canada-Caribbean institute would go a long way in conducting scholarly graduate-level research in fields of security-sector reform.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.024 | 0.004 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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.
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".