Bibliographic record
Abstract
Canada and Australia championed a negotiation process that led to international treaties to respectively ban landmines and regulate the arms trade. Yet they have also sought to block progress on another treaty, on cluster munitions. These parallel yet distinct negotiating tracks suggest the question, when do states actively engage in treaty-making?To address this, this paper analyzes ten turning points across three phases in each of three multilateral negotiation cycles to compare and contrast the conditions under which Canada and Australia at times contributed to, and at times impeded, treaty negotiation processes.This paper finds that the championing of processes occurred when political leadership, substantive expertise and diplomatic resources were all present. When states attempted to slow down progress or to hollow out the substance of treaties, political leadership was noticeably absent. These findings indicate that negotiations should be analyzed within multi-layered internal and external contexts, from the streets to the world to capitals and over the threshold into diplomatic venues and the corridors, rooms, and tables. Each layer adds meaning and understanding to how treaties are born. The links between layers provide a complete picture that accurately reflects when and how championing and blocking strategies are adopted by these two states.By examining parallel negotiating tracks, this paper provides insights on the conditions under which multilateral treaty-making on the manufacture, use and trade in conventional weapons is shaped by Westminster parliamentary democracies. With many gaps to fill in this area of international regulation, these insights may help smooth the path towards further multilateral treaties.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".