Defence Against Help and the Broadening Securitization of Canada-US Relations
Bibliographic record
Abstract
Defence against help is a strategy by which a smaller state seeks to avoid receiving unwanted help from a larger state that is committed to the former's safety as part of its own security strategy. Canada-US security relations are commonly cited as an example of defence against help. Traditionally, the term has been applied only to a narrowly defined concept of security. However, after 2001 defence against help has come to reflect the broadening of the US national security agenda. Defence against help might therefore be used to explain aspects of Canada-US relations that have not traditionally been treated within a security framework, such as energy relations. Canada is a major supplier of oil to the United States, and energy has been regularly identified as a national security issue within the US government. The objective of this paper will be to examine shifts in Canadian energy policy and determine whether it is possible to show that securitization has affected outcomes within this aspect of Canada-US relations and, consequently, whether defence against help provides a useful analytical framework for this aspect of the relationship.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".