Understanding reneging: Canada's nuclear sharing commitments to NATO and NORAD during the Cold War
Bibliographic record
Abstract
How and why do leaders renege on their alliance commitments, despite institutional incentives to cooperate? According to the research on alliance reliability, three types of costs discourage reneging: material costs, reputational costs, and domestic audience costs. These costs are theorized to be especially high for leaders of democracies, junior alliance members, and members of highly institutionalized alliances. Yet, despite these characteristics, Canada's foreign policy related to its nuclear sharing commitments to NATO and NORAD between 1957 to 1984 was uneven. It included several instances of reneging or attempted reneging. Through an in-depth analysis of archival material related to Canada's nuclear alliance commitments, I propose a new theory of reneging. I show that a leader's decision to renege, choice of bargaining strategy in intra-alliance negotiations, and likelihood of success are related to the type of domestic coalition that supports reneging. Leaders with the support of nationalist domestic coalitions face fewer audience costs for reneging and have more leverage when bargaining with allies than those with the support of single-issue or anti-nuclear coalitions. Nationalist coalitions provide negotiators with three key sources of bargaining power in intra-alliance negotiations: a credible threat of withdrawal, a willingness to act unilaterally, and a low vulnerability to being swayed by foreign allies. On the other hand, single-issue coalitions do not wish to leave the alliance, are more willing to act through alliance consensus, and are more vulnerable to allies' attempts to in uence their stance.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".