The Evolving Arms Control Agenda: Implications of the Role of NGOS in Banning Antipersonnel Landmines
Bibliographic record
Abstract
This article examines the role NGOs have played in placing and controlling the landmineban issue on the international arms control agenda, which eventually changed state behavior toward landmines. It develops a framework for agenda setting to examine how and why NGOs were successful in this role. More importantly, the article also examines how NGOs were able to generate state action toward the support of the Ottawa Treaty banning antipersonnel landmines, which marked the first time a weapon in widespread use has been banned. The article makes two interrelated arguments. First, NGOs initiated the landmine ban by placing it on the international arms control agenda, which gained intense media and public attention for the cause. The NGOs accomplished their goal by utilizing cognitive attribution strategies to educate the public about the minimal military utility of landmines and the humanitarian problems they pose. Second, NGOs changed states’ perception toward the legality and use of landmines once the issue was on the agenda by highlighting the horrible effects and disproportionate consequences of landmine use, playing leadership games with influential individuals and states, and claiming that antiban states were using incoherent arguments. In comparison, NGOs have not been included in the agenda-setting processes of most other major arms control and disarmament treaties, which typically are negotiated at the behest of major powers. These arguments address the broader question of agency in world politics by showing potential conditions of how NGOs can instigate governments to address issues in a way that may culminate in international law.
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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 | 0.026 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.039 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.011 | 0.010 |
| 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".