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Record W2755021782

China’s Evolving Nuclear Forces: Changes, Rationales and Implications

2017· article· en· W2755021782 on OpenAlexaffvenue
Adam P. MacDonald

Bibliographic record

VenueJournal of military and strategic studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsDalhousie University
Fundersnot available
KeywordsModernization theoryChinaCredibilityNuclear weaponNuclear forceBallistic missilePolitical scienceNuclear powerBeijingMissileVulnerability (computing)Software deploymentGreat powerHegemonyPolitical economyInternational tradeBusinessComputer securityLawEngineeringComputer scienceSociologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

China is embarking on a comprehensive modernization program to quantitatively and qualitatively improve their nuclear force. These efforts, however, do not reflect or indicate a distinct shift in Chinese views towards or policy governing the purpose and use of nuclear weapons, but to achieve and maintain a secured second strike capability in a changing strategic landscape. Specifically, military developments by the United States including Ballistic Missile Defence and Precision Global Strike are seen as threatening the credibility of their nuclear deterrent, motivating the construction and deployment of a more modern, diverse and capable force. These force reconfigurations, however, create the potential of causing confusing and misunderstandings with the United States, and other nuclear powers, of the rationales informing their improvement. Ensuring the nuclear force balance between Beijing and Washington remains a minor and largely benign matter separated from and not influencing other more divisive matters is critical in the maintenance of their relatively stable, but increasingly complicated and tense, great power relationship and the international system in general. In order to achieve this, both states must clearly signal an understanding of their nuclear relationship as one defined by mutual vulnerability and the necessity of providing guarantees and evidence that their respective military technological developments and force structure changes are not designed to alter this reality.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.011
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.085
GPT teacher head0.351
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2017
Admission routes2
Has abstractyes

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