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Record W3187029368

Reconciling State Practice of In-Orbit Satellite Transfer with the Law of Liability and Registration in Outer Space

2018· article· en· W3187029368 on OpenAlexaff
Upasana Dasgupta

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsMcGill University
Fundersnot available
KeywordsJurisdictionSatelliteLeaseOuter spaceSpace lawLiabilityState (computer science)LawBusinessOrbit (dynamics)Political scienceEngineeringComputer scienceAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

Satellites are useful means for ensuring welfare of mankind in the areas of education, socio-economic parameters, peace and security and environment protection. Thus, satellites can play a significant role in bringing sustainable development. However, only a few States have developed the technology to launch and manufacture satellites. Hence, it is prudent for the new entrants to purchase or lease already functional inorbit satellites as it saves the associated legal and logistical hassles, such as, obtaining launch licenses. The buyers do not need to wait for operation of satellite till launch is accomplished, enter into multiple contracts and can avoid the risk of launch failure. For existing operators too, in-orbit satellite transfer helps in dealing with sudden demand for satellite services. However, the State practice in this regard has been inconsistent with each other and often in violation of laws of liability and registration in outer space. For example, in some instances, transferee States have denied being the launching State and State of registry, yet have claimed jurisdiction and control over the satellites, whereas under space law, only State of registry can have jurisdiction and control and such State has to be a launching State. One reason behind this may be that the current space law is inadequate to address the issue of in orbit satellite transfer. The paper expounds on the legal issues that arise due to State practice in such cases, the need for reconciling the State practice with the international law and propose the pragmatic solution/s in the current circumstances.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.383

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 head0.007
GPT teacher head0.240
Teacher spread0.232 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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