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Record W4366320848 · doi:10.36642/mjil.44.2.relentless

Relentless Atrocities: the Persecution of Hazaras

2023· article· en· W4366320848 on OpenAlexaff

Bibliographic record

VenueMichigan Journal of International Law · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsQueen's University
Fundersnot available
KeywordsPersecutionGenocideCrimes against humanityLawElement (criminal law)StatuteDeportationEthnic CleansingPolitical scienceCriminologyInternational lawEthnic groupInternational communityRefugeeThe HolocaustWar crimeSociologyImmigrationPolitics

Abstract

fetched live from OpenAlex

As one of the main ethnic groups in Afghanistan, Hazaras are Farsi-speaking and mostly Shi’a Muslims in a predominantly Sunni Muslim country. They are also distinguishable by their Asiatic appearance. Throughout Afghanistan’s history, Hazaras have suffered considerably under different regimes, enduring recurring massacres, enslavement, and forced displacement. Despite Afghanistan’s accession to the Rome Statute in 2003, the plight of Hazaras has not improved. Indeed, the assaults on Hazaras have only intensified in recent years, impacting virtually every aspect of their lives. This article argues that the recent and ongoing attacks against Hazaras constitute a crime against humanity. In particular, I show, element by element, that there is a reasonable basis to believe that the assaults on Hazaras amount to persecution based on ethnic and religious grounds pursuant to article 7(1)(h) of the Rome Statute. Accordingly, the International Criminal Court and the global community must take urgent actions to investigate the relentless atrocities against Hazaras and to hold the perpetrators accountable. Failure to do so, as warned by the U.S. Holocaust Memorial Museum, may lead to a full-blown genocide.

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)0.001
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 score0.968
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.315
Teacher spread0.292 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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