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Record W2968578844 · doi:10.5539/jpl.v12n3p80

Bangladesh's Approach towards International Criminal Law: A Case Study of International Crimes Tribunal Bangladesh

2019· article· en· W2968578844 on OpenAlexvenueno aff
Muhammad Abdullah Fazi, Pardis Moslemzadeh Tehrani, Mian Waqar Ahmed, Sardar Ali Shah

Bibliographic record

VenueJournal of Politics and Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsTribunalLawInternational Covenant on Civil and Political RightsPolitical scienceWar crimeGenocideInternational lawInternational humanitarian lawCriminal lawRight to a fair trialHuman rightsInternational human rights lawRight to property

Abstract

fetched live from OpenAlex

The International Crimes Tribunal Bangladesh that has been found by the Bangladeshi Government to try war crimes during India Pakistan war of 1971. The tribunal is violating the fair trial rights as guaranteed by Constitution, the International Covenant on Civil and Political Rights and International Humanitarian Law and the standard of the International Crimes Tribunal Bangladesh is far below than that setup by The International Criminal Tribunal for the former Yugoslavia, the International Criminal Tribunal for Rwanda and the International Criminal Court. These irregularities imply serious concern over the proceedings of the said tribunal. Study seeks to describe the International Law about war crimes particularly with respect to fair trial provisions and it compare the proceedings of the Bangladeshi tribunal with the other internationally recognized tribunals.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0290.010
Scholarly communication0.0080.003
Open science0.0020.005
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.041
GPT teacher head0.338
Teacher spread0.296 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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