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Record W3193293942 · doi:10.82308/36615

State responsibility for non-state actors in times of war: Article VI of the Outer Space Treaty and the law of neutrality

2018· article· en· W3193293942 on OpenAlexfundno aff
James Gutzman

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
FundersMcGill University
KeywordsNeutralityTreatyPolitical scienceLawState responsibilityState (computer science)Space (punctuation)Law of warLaw and economicsSociologyInternational lawPhilosophyMathematics

Abstract

fetched live from OpenAlex

The explosion of non-State actors in outer space has come with enormous corporate and inter-State complexity. Instead of a private US-based company sending a single satellite into orbit, multi-national corporations have plans to send thousands. In-orbit satellites are being bought and sold by companies incorporated in different States. Foreign military departments are putting communications payloads on non-State actor satellites. This thesis looks at the implications of these non-State actors in space performing actions that could affect the neutrality of their licensing State. Article VI of the 1967 Outer Space Treaty attributes all actions of non-State actors in Space to the State responsible for them. The law of neutrality outlines the appropriate conduct of States who are part of an international conflict, or belligerents, and States not part of an international conflict, or neutrals. Therefore, if there were a conflict and a non-State actor from a neutral State were to provide military communications to a belligerent, the non-State actor’s licensing State’s neutrality could be implicated. The analysis herein looks at the corporate structures, the services, and the licensing mechanisms used by various States vis a vis international outer space law and the law of neutrality. I argue that in space, because all actions are attributed to the State and because corporations have increased in complexity, there should be a higher threshold for States to be declared belligerent if their non-State actors provide space-based services to a State at war.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.019
Scholarly communication0.0090.007
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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 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
Published2018
Admission routes1
Has abstractyes

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