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Record W4362633368 · doi:10.1017/9781108597135.009

Anti-satellite Weapons and International Law

2023· book-chapter· en· W4362633368 on OpenAlexaff
Michael Byers, Aaron C. Boley

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPrinciple of legalityTreatySpace debrisLawInternational lawSatellitePolitical scienceArms controlSpace (punctuation)Outer spaceCustomary international lawJus ad bellumLaw and economicsComputer securityUse of forcePublic international lawEngineeringSociologyComputer scienceAerospace engineeringSpacecraft

Abstract

fetched live from OpenAlex

Anti-satellite weapons that rely on violent impacts and create space debris are regarded as a major threat to the exploration and use of space, including the use of space assets for communications and Earth imaging. This chapter examines two ways in which the testing of such ‘kinetic’ weapons might already have become illegal. First, the accepted interpretation of Article I of the Outer Space Treaty may be evolving as a result of the changing practice of the parties to that treaty. In short, many states are behaving as if tests of anti-satellite weapons that create debris are contrary to the ‘freedom of exploration and use of space’. Second, the same practice and an accompanying opinio juri s may be contributing to the development of a parallel rule of customary international law. This chapter also examines the legality of the use of kinetic anti-satellite weapons, as opposed to their testing. Two additional, separate bodies of international law are relevant here: the jus ad bellum governing the recourse to armed force, which includes the right of self-defence, and the jus in bello governing the conduct of armed conflict. A close analysis leads to the conclusion that any use of a kinetic anti-satellite weapon would be illegal today because of the growing crisis of space debris.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.995
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.216
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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