The Full Picture: Preliminary Examinations at the International Criminal Court
Bibliographic record
Abstract
Abstract The International Criminal Court’s (ICC) Office of the Prosecutor (OTP) has described the preliminary examination as one of its “three core activities,” alongside investigating and prosecuting crimes under the Rome Statute of the International Criminal Court (Rome Statute). Honing in on this once-mysterious “core activity,” this article contributes to the recently expanding literature on preliminary examinations at the ICC by providing a much needed comprehensive picture of all preliminary examinations conducted to date. The twentieth anniversary of the court’s founding treaty, the Rome Statute, provides a timely opportunity for this review as part of the broader effort to take stock of the ICC’s achievements, failures, and future. The article demonstrates that, despite not having full investigatory powers at the preliminary examination stage, the OTP is very active during this phase. It interacts with a wide range of domestic and international actors and makes decisions on important legal issues that go to the heart of the ICC’s work. Paying close attention to preliminary examinations is therefore critical to understanding the OTP’s work, to understanding which actors engage with, and seek to “use,” the ICC, and to understanding important debates about the ICC’s legitimacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 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".