MétaCan
Menu
Back to cohort
Record W4417170547 · doi:10.61838/kman.isslp.366

Prosecutorial Policy Indicators of the Prosecutor of the International Criminal Court

2025· article· W4417170547 on OpenAlexaff
Fatemeh Sadeghi, Masoud Zamani, Amir Maghami

Bibliographic record

Venuenot available
Typearticle
Language
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegitimacyHuman rightsAccountabilityEconomic JusticeInternational lawJudicial reviewBalance (ability)

Abstract

fetched live from OpenAlex

The prosecutorial policy of the Prosecutor of the International Criminal Court (ICC) plays a central role in the realization of international criminal justice and in ensuring accountability for serious international crimes. This article aims to analyze the main indicators of the Prosecutor’s prosecutorial policy by examining the legal framework, judicial principles, and political, operational, and ethical indicators. An examination of the legal framework shows that the Prosecutor’s decisions must be based on legal authority, the principles of legitimacy and justice, and the limitations of the Rome Statute. Judicial indicators include prioritization of cases, analysis of evidence, and an emphasis on deterrent and preventive justice. In addition, political and international indicators—such as interaction with the Security Council and diplomatic pressures—can play a decisive role in the selection of cases, while operational and ethical indicators, including resource management, transparency, and respect for the rights of both defendants and victims, contribute to maintaining the legitimacy and effectiveness of prosecutorial policy. An analysis of practical examples demonstrates that the success of prosecutorial policy requires a balance between judicial effectiveness, prosecutorial independence, and adherence to human rights standards. The findings of the article emphasize that transparency, accountability, and ethical commitment are indispensable indicators in the design and implementation of prosecutorial policy, and that they can contribute to enhancing justice and legitimacy of the Court at the international level.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.056
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.009
Science and technology studies0.0020.002
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.009
GPT teacher head0.307
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicInternational Law and Human RightsFrench-language works237,207