The Limits of Consequentialism: ICTY Conditionality and (Non)Compliance in Post-Milosevic Serbia
Bibliographic record
Abstract
Since 2000—the dusk of the Milosevic-era—three successive Serbian governments, the Djindjic, Zivkovic and Kostunica administrations, have amassed an inconsistent and oscillating record of (non)compliance with EU and US conditionality for full cooperation with the International Criminal Tribunal on the Former Yugoslavia (ICTY). How do we explain this changing pattern of compliance and noncompliance by Serbia? This paper contends that international rules and norms which attempt far-reaching institutional and social change, such as ICTY conditionality in Serbia, will likely elicit a historical process that is multidimensional and diachronic, more politically complex than the parsimony suggested by incentives-based, model-driven theorizing. The paper argues for a more contextual and practice-oriented approach to the study of compliance politics; focusing on how material, normative and temporal dimensions interact historically to form particular compliance processes & outcomes. The empirical section uses inductive process-tracing to make a temporal reconstruction of the process and experience of Serbian (non)compliance with ICTY conditionality during the Kostunica government; focusing on the interaction between three dimensions of compliance politics: (1) strategic calculation; (2) identity & cultural resonance; and (3) temporality. Full text available at: https://doi.org/10.22215/rera.v4i1.192
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".