THE SOCIO-POLITICAL CONTEXT OF COMPLEMENTARITY:THE ICC AND NARRATIVES OF JUSTICE IN KENYA
Bibliographic record
Abstract
The establishment of the International Criminal Court (“the Court”) brought with it immense expectations about its overall ability to catalyse prosecution of international crimes in domestic criminal jurisdictions. The assumption was that the intervention or threatened intervention of the Court would trigger domestic action towards investigating and prosecuting international crimes. Two decades since its establishment, studies have been conducted to test this general assumption. The focus has been on how the Court has influenced these domestic jurisdictions to enact enabling laws and prosecute international crimes. These studies have formed a useful yardstick for assessing the effectiveness and legitimacy of the Court. The studies have expectedly arrived at varied results but there seems to be consensus that the Court has not lived up to the ideal expectations. However, very few attempts have been made to understand the behaviour of domestic jurisdictions when they interact with the ICC. This chapter aims to fill that gap by assessing the Court’s interaction with Situation countries in the context of the socio-political factors that underlie its possible impact. In choosing Kenya as a case study, the chapter aims to provide a comprehensive assessment of the context of the 2007-2008 Post Election Violence (“PEV”), how it shaped the various interactions with the Court and what these portend for justice. Through this analysis it is argued that the impact of the ICC is informed by unique socio-political factors prevailing in each situation. As such, the Court’s impact is, in contrast to popular belief and expectations, unpredictable.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.027 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 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".