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Record W2941441854 · doi:10.7202/1066340ar

Extra-Territorial “Fiduciary” Obligations and Ensuring Respect for International Humanitarian Law

2019· article· en· W2941441854 on OpenAlexvenueno aff
K Trapp

Bibliographic record

VenueMcGill Law Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsFiduciaryHuman rightsInternational lawPolitical scienceLawTreatySovereigntyLaw and economicsContext (archaeology)International human rights lawInternational humanitarian lawSociologyDutyPolitics

Abstract

fetched live from OpenAlex

Respect for human rights is often understood to be in tension with a robust approach to protecting human security (both within a single state’s territory and across territorial boundaries). Principles like those which form the basis of Fox and Criddle’s fiduciary theory of sovereignty—such as non-instrumentalization and non-domination—may suggest an approach to balancing these competing interests, but not necessarily with the specificity and detail required of particular legal contexts. This article seeks to explore an alternative route to balancing these competing interests—one which draws on positive international law. The context for this exploration is that of ‘asymmetrical self-defence,’ taking the quintessential threat to both human rights and human security, in the form of armed conflict, as its case study. Where states provide support to participants in armed conflicts occurring on the territory of other states, they potentially increase the risks to those caught up in the conflict, raising important questions as to the nature, basis and content of the international legal duties associated with their support. It is argued that Common Article 1 of the Geneva Conventions , risk related human rights obligations (like that of non - refoulement ) and the Arms Trade Treaty are the positive law basis for obligations Fox and Criddle otherwise characterize as fiduciary. These frameworks provide much more of the detail required for effective regulation, such as obligations to be informed, the permissibility or otherwise of balancing other interests against the risk of IHL breaches, and the differentiated treatment of risks to jus cogens compliance.

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 categoriesScience and technology studies
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 score0.848
Threshold uncertainty score0.997

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 studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.305
Teacher spread0.275 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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