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Record W4414679722 · doi:10.1017/lsr.2025.10062

Prosecutorial-NGO Complex: new legal opportunity structures and the role of (I)NGOs in universal jurisdiction trials on Syria

2025· article· en· W4414679722 on OpenAlexaff
Joachim J. Savelsberg, Jillian LaBranche, Miray Philips

Bibliographic record

VenueLaw & Society Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsJurisdictionUniversal jurisdictionMobilizationHuman rightsNarrativeCore (optical fiber)Legal culture

Abstract

fetched live from OpenAlex

Abstract Changing legal environments create new opportunities for legal mobilization by civil society groups. At stake is mobilization in Germany and Europe for the prosecution of agents of the Syrian Assad regime accused of committing core international crimes. Changes in the legal environment include the (a) spread of universal jurisdiction; (b) increasing use of “crimes against humanity”; (c) new prosecutorial and policing units specialized in core international crimes; and (d) new prosecutorial practices, such as structural investigations. Coinciding with an influx of Syrian refugees, these opportunities give rise to a collaborative network of (I)NGOs that feed witnesses and evidence into prosecutorial agencies. Interaction between agencies and (I)NGOs contributes to the transnational ordering of criminal law and constitutes a Prosecutorial-NGO (P-NGO) Complex. (I)NGOs finally diffuse court narratives to a broad audience and shape public knowledge of grave violations of human rights. We focus on the P-NGO Complex for the al-Khatib universal jurisdiction trial before the Higher Regional Court in Koblenz, Germany. Empirical tools include an analysis of (I)NGO network structures and websites, interviews with court observers, activists, and prosecutorial staff, and an analysis of media reporting.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.353
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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