Bibliographic record
Abstract
The Responsibility to Protect (R2P) renders state sovereignty conditional when mass atrocities are perpetrated. It was conceptualized as a new norm in response to the genocides in Rwanda and Srebrenica, and adopted by the UN General Assembly in 2005. Since then, it has been referenced in numerous resolutions at different UN bodies. However, the R2P continues to be contested, and, against the backdrop of an increasingly illiberal world order, norm supporters’ activities have shifted from introducing to preserving it. The chapter focuses on three prominent R2P supporters, Denmark, Sweden, and Canada, asking how they rhetorically frame the norm. Specifically, it studies how state representatives frame the global challenge of preventing and responding to mass atrocities over time and, through this, frame the R2P as the appropriate policy response. The chapter analyzes UN speeches and interviews, outlining states’ use of six “modes of constructing” the addressed global challenge. The modes are (1) upholding urgency in reference to emerging crises, (2) upscaling issues to the global level, (3) censuring and condemning, (4) bundling norm agendas, (5) conceptualizing and repeating norm content, and (6) finding (new) institutional homes. Throughout, the chapter discusses and illustrates those modes and their respective empirical relevance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".