Capitalism, Global Militarism, and Canada’s Investment in the Caribbean
Bibliographic record
Abstract
At the end of the 1990s, there existed a belief that a growing Canadian military involvement in the Caribbean region was unlikely if it was not associated with Canada’s interest in Latin America (Klepak 1996). This view had such a large impact that today there is a dearth of information on Canada’s military involvement in the Caribbean region. Lacking systematic investigation, two myths have perpetuated: first that Canada has no stake or interest in Caribbean security, insofar as those interests cannot be tied to Canada’s interests in Latin America; and second, that all expressions of Canada’s involvement in Caribbean security are simply extensions of US security interests in the region. Looking at Canada as part of the Anglosphere, this paper analyzes Canada’s ongoing commitment in the Caribbean to preserving and expanding the political, social, economic, and ecological system that benefits Anglospheric capitalist accumulation and security objectives. Today, Jamaica is the host site for the Canadian Armed Forces Operation Support Hub in Latin America and the Caribbean (OSH-LAC), as Canada aims to position its long-term security partner as a regional sub-policeman of the region. OSH-LACs proximity to states like Haiti, a frequent site of Canadian intervention, should worry those concerned with Canada’s increased global militarism and imperialism in the world more broadly.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".