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Record W2101813780 · doi:10.5334/sta.ar

Challenging International Justice: The Initial Years of the International Criminal Court’s Intervention in Uganda

2013· article· en· W2101813780 on OpenAlexvenueno aff
Lucy Hovil

Bibliographic record

VenueStability International Journal of Security and Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHonestyEconomic JusticePolitical sciencePoliticsLawIntervention (counseling)Criminal justiceCriminal courtContext (archaeology)CriminologyInternational lawSociologyPsychologyGeography

Abstract

fetched live from OpenAlex

This practice note describes and critiques the initial years of the International Criminal Court’s (ICC) involvement in Uganda from the perspective of local civil society actors. It argues that the substance and process of the ICC’s intervention fell chronically short of generating justice for those who had lived with the conflict for over two decades, and therefore created a disconnect between the priorities of those on the ground, and the priorities of the Court and its international minders. In order to unravel some of the dynamics that underpinned this disconnect, the paper asserts that the pivotal relationship between citizen and state provides a lens through which to assess any approach to generating justice in Uganda. It concludes that those promoting international justice need to be more cognisant of the fact that international justice mechanisms are obsolete unless they can move from theory to practice and make a genuine difference in people’s lives. In this regard, a better understanding and awareness of the political and social context in which they are operating, as well as greater self-critique and honesty, is critical.

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)0.022
metaresearch head score (Gemma)0.045
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0420.033
Scholarly communication0.0230.014
Open science0.0020.027
Research integrity0.0120.022
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.328
Teacher spread0.295 · 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

Citations19
Published2013
Admission routes1
Has abstractyes

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Same venueStability International Journal of Security and DevelopmentSame topicGlobal Peace and Security DynamicsFrench-language works237,207