MétaCan
Menu
Back to cohort
Record W2105499097

Approaches to Transparency in Arms Control and Verification - A Canadian View of Chinese Perspectives

2001· article· en· W2105499097 on OpenAlexaffvenueabout
Robert E. Bedeski

Bibliographic record

VenueJournal of military and strategic studies · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTransparency (behavior)SecrecyChinaDemocracyAuthoritarianismDisadvantagePolitical scienceLaw and economicsPoliticsPolitical economyState (computer science)SurrenderLawComputer securityEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

China and Canada represent nearly two opposite ends of a continuum starting with near-total secrecy and ending at near-total transparency in matters of state. Canada advocates transparency, and China opposes it - or at least is extremely cautious in cooperating unless some vital interests are served. China is increasingly drawn into processes of transparency and verification, but the prevailing view is that transparency is only possible between states of equal power; otherwise, the weaker are at a disadvantage in revealing their weakness. It can be argued that Chinese reluctance to increase transparency only fuels suspicions about its intentions. China regards secrecy to be an essential element of statecraft, and will not modify it simply to mollify critics, or to surrender it for access to more sophisticated Western technology. Greater availability of timely and accurate information can have positive benefits for international peace and security, but it is the imbalance between democratic and authoritarian habits of information control that differing notions of transparency emerge. Transparency is not merely a technical problem, but one which derives from the nature of the political system.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.979

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 head0.088
GPT teacher head0.308
Teacher spread0.221 · 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 designQualitative
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

Citations1
Published2001
Admission routes3
Has abstractyes

Explore more

Same venueJournal of military and strategic studiesSame topicCybersecurity and Cyber Warfare StudiesFrench-language works237,207