The legality and implications of intentional interference with commercial communication satellite signals
Bibliographic record
Abstract
AbstractOver the past few decades, commercial communication satellites have improved the lives of people all over the world. They have fundamentally transformed the way people communicate, how business is conducted, and the manner in which militaries operate, fight and win wars. This dependence, however, has revealed that commercial communication satellites are increasingly vulnerable to disruptions, but also that these disruptions can pose significant risks to users everywhere. Such risks are especially concerning given the likelihood that satellite signal interference will be employed during future armed conflicts to disrupt the communications of adversaries. The implications of this new political, technical and military reality challenge the normative frameworks under international telecommunications law, international space law and international humanitarian law. This thesis addresses these and related issues in four chapters. Chapter One explores the extent to which satellite signal interference is becoming a serious threat to global users. Chapter Two discusses the technical application of interference and the normative regimes governing or relating to satellite transmissions and satellite communications. Chapter Three examines circumstances under which satellite signal interference can constitute an unlawful use of force or amount to an armed attack pursuant to the UN Charter. Chapter Four outlines the range of responses available to States suffering the effects of satellite signal interference.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".