Broadening the Ban: Limitations of Agency, Intentionality, and Legitimacy in the Ottawa Convention
Bibliographic record
Abstract
This paper aims to contribute to a critical understanding of the implications of the Ottawa Convention through an assessment of the ways in which agency, intentionality, and legitimacy are woven into the discourse surrounding the ban treaty. It is hoped that through a problematisation of the discursive and conceptual limitations of the Ottawa Convention, the agenda and targets of the ban might at the very least be broadened to include other categories of weapons that perform and devastate in the same ways as AP landmines. At best, it is hoped that this paper will stimulate critical thinking about militarisation and state-centric security practices more generally, and \nwill call into question those particular underlying norms that give rise to discursive constructions of states and state interests, militaries, and weapons usage as unproblematically ‘necessary.’
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.056 |
| Scholarly communication | 0.025 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".