MétaCan
Menu
Back to cohort
Record W2974683570

Cyber Espionage and International Law. By Russell Buchan. Oxford: Hart, 2018 (Book Review)

2019· article· en· W2974683570 on OpenAlexaff
Leah West

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCyberspaceEspionageIndustrial espionagePolitical scienceCustomary international lawInternational lawLawTerrorismState (computer science)AssertionCyberwarfarePublic international lawThe InternetComputer science
DOInot available

Abstract

fetched live from OpenAlex

In 2015, then US President Barack Obama referred to cyberspace as the “new Wild West” — vast, lawless, and without a sheriff in sight. Given these qualities, it is unsurprising that actors leverage cyberspace to perpetrate crime, terrorism, foreign influence, and espionage with increasing effectiveness. Meanwhile, the international community has struggled to find common ground on the application, let alone enforcement, of international law in cyberspace. While there have been a number of high-level commitments made by allied states to work together to develop “norms of cyberspace,” the prominent and decade-long effort of the United Nations Group of Governmental Experts to address state behaviour in cyberspace collapsed in 2017 due to a lack of consensus. Two separate and open-ended working groups have since taken its place; one effort led by the United States, the other by Russia. In his text, Cyber Espionage and International Law, Russell Buchan not only takes on the notion that cyberspace is a lawless domain, but he also challenges the oft-repeated assertion that state-sponsored espionage is lawful under international law.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.267
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicCybersecurity and Cyber Warfare StudiesFrench-language works237,207