Beyond LAVs: corruption, commercialization and the Canadian defence industry
Bibliographic record
Abstract
The Trudeau government’s decision to uphold a 2014 contract to sell CAD $15 billion worth of military equipment to Saudi Arabia has attracted considerable controversy in Canada, garnering both opposition and support. Yet public discussion of the Canada–Saudi light armored vehicle (LAV) contract has sidestepped the most serious problems raised by Canada’s escalation of its involvement in the international arms market through this sale: the violence and corruption of the international arms trade, to which this sale contributes; the subordination of Canadian foreign policy and of international peace and security to commercial aspirations and the short-term interests of electoral politics, which this contract evinces; and the questionable importance of the Canadian defence industrial base, upon which arguments in favor of this contract rely. Given both the political and economic salience of defence industry jobs in the 2015 election and the export-driven nature of Canada’s defence industry, Canadians should not be surprised by the Canada–Saudi LAV deal. The real question, however, is whether Canada should support its own defence industrial base, whatever the costs and contribution to corruption – or not.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".