Germany's Politics and Bureaucracy for Preventing Atrocities
Bibliographic record
Abstract
has accepted the unique responsibility arising from its history.The avoidance of war and violence in international relations, the prevention of genocide and severe violations of human rights, and the defence of endangered minorities and the victims of oppression and persecution are integral to Germany's reason of state. 1 As of June 2017, this is official German government policy, adopted by the federal cabinet as the highest executive organ in its "Guidelines on Preventing Crises, Resolving Conflicts, Building Peace."Compared to earlier policy documents, the ambition is expressed more strongly than ever: raison d'état, or reason of state, is vernacular usually reserved for Germany's unwavering commitment to the survival of the state of Israel.The statement quoted above must be seen in the context of Germany's broader coming of age in matters of international leadership.It does not describe the emphasis on preventing genocide and mass atrocities in current policy.Interpreting this aspiration and its prospects for shaping future policy requires substantial background on the past and present of Germany's political debates and bureaucratic infrastructure on crisis prevention, atrocity prevention, and responsibility to protect.This paper consists of two main sections.The first introduces the political context and recent history of Germany's institutional setup for atrocity prevention.The second describes this setup and explains its strengths and weaknesses, as well as the key challenges to be addressed in order to live up to the aspiration of making more effective contributions to the prevention of genocide and other atrocities.We conclude with an outlook on Germany's contributions to atrocity prevention in the next few years. Context: Debates on Prevention and Intervention in GermanyAtrocity prevention as a distinct category in German political debates is fairly new and still rarely used.Over the past 15 years, the issues that were discussed in the US as atrocity prevention were linked either to the responsibility to protect (R2P) or to conflict prevention, which is referred to as "crisis prevention" in the German debate.2 Part of the reason for this is evident in the language.There is no consistent, agreed-upon phrase for "mass atrocities" in German.However, the two debates about R2P and conflict prevention have been almost completely disconnected from one another: the R2P debate is tainted by its association with military intervention, while the conflict prevention debate is shaped by an emphasis on long-term, structural peacebuilding with civilian means.Accordingly, atrocity prevention is almost never treated as a category in itself, and there is little awareness of the differences between conflict and atrocity prevention.3 "Never Again What?" Contradicting Historical Lessons at the Center of the Prevention Debate Key to comprehending German views on all three categories -R2P, conflict prevention and atrocity prevention -is understanding the societal and historical debates in Germany on these topics.This 1 German Federal Government, Guidelines on Preventing Crises, Resolving Conflicts, Building Peace, July 21, 2017 (German Federal Foreign Office), accessed December 31, 2017, www.diplo.de/guidelines.2 The German policy community uses the term "crisis prevention" ("Krisenprävention") where most English speaking experts would use conflict prevention.The German usage comes with many conceptual debates on its own.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".