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Record W1811481188 · doi:10.1017/s0008423900000275

Nuclear Arsenal Games: Coping with Proliferation in a World of Changing Rivalries

2000· article· en· W1811481188 on OpenAlexaboutno aff
Carolyn C. James

Bibliographic record

VenueCanadian Journal of Political Science · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

This article presents and establishes the significance of the Nuclear Arsenal Games, which investigates behaviour within dyads experiencing a crisis. It assumes that nuclear and quasi-nuclear states act according to the size and potential of their own nuclear force structure and that of their opponent. This article argues that the size and potential damage an arsenal poses determines actor preferences within a crisis situation. The specific objective here is to propose a nuclear index for use in empirical studies and offer an example of one game-theoretic approach of crisis interaction that indicates whether preferences and predicted behaviour adhere to the assumptions of Classical (or Rational) Deterrence Theory. Resume. Cet article explique et d6montre la port6e des ?jeux de l'arsenal nucl6aire> qui examinent le comportement des 1tats durant une crise. Ces jeux stipulent que, dans une telle situation, les Etats qui posshdent ou qui sont sur le point de possfder une force nucl6aire agissent en fonction de la taille et du potentiel de leur propre arsenal nuclfaire et de celui de leurs adversaires. Cet article soutient que les prrf6rences des acteurs, lors d'une crise, sont d6terminfes par l'importance du dommage potentiel que peut causer un arsenal nucl6aire. De manibre plus sp6cifique, il propose un index des forces nucl6aires utiles pour les 6tudes empiriques et pr6sente une approche des intdractions en situation de crise de la thdorie des jeux qui permet de v6rifier si les pr6f6rences et les comportements prrvisibles des acteurs confirment les hypotheses de la thdorie classique (ou rationnelle) de la dissuasion. Mini-arsenal presents more specifically a minimal nuclear capability and its relation to crisis behaviour. This is perhaps the most complex, and therefore difficult, level to describe. First, a mini-arsenal state is capable of acquiring, at best, two or three, crude Hiroshima or Nagasaki-style warheads. Fat Man, the bomb dropped on Nagasaki, was about 20 kilotons, the more powerful of the two used by the United States in 1945. This pales in comparison to thermonuclear weapons, that are measured in megatons. India, Israel and Pakistan, which can project significant nuclear threats, are beyond this category since the arsenals they are believed to possess contain qualitatively and quantitatively much more destructive power. Second, the most critical distinction of the mini-arsenal is that, while potential damage may be extreme, destruction of state or society is not assured. A strike from a mini-arsenal state may be survivable-militarily, politically and socially. This perception, which may be held both by the mini-arsenal state leadership and its potential enemies, is expected to result in preferences and behaviour that do not match actions of states with more deadly arsenals. Leadership that is more willing to risk domestic populations may consciously choose to escalate wars to nuclear levels if the state and its government may survive. Of the four levels of nuclear capability, mini-arsenal dyads promise to be the most unstable during crises as the deadliest of cost-benefit analyses are expected to take place. The NAG assumes that capability is related to, yet distinct, from choice. Canada and Sweden, for instance, have the capability of nuclear proliferation with relatively few physical impediments. Resources, in This content downloaded from 207.46.13.20 on Wed, 28 Dec 2016 18:06:24 UTC All use subject to http://about.jstor.org/terms 726 CAROLYN C. JAMES

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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

Citations5
Published2000
Admission routes1
Has abstractyes

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