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Record W2000149747 · doi:10.1177/0096340212464363

The closest brush: How a UN secretary-general averted doomsday

2012· article· en· W2000149747 on OpenAlexaboutno aff
A. Walter Dorn, Robert Pauk

Bibliographic record

VenueBulletin of the Atomic Scientists · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBrushSecretary generalPolitical scienceOperations researchLawEngineering

Abstract

fetched live from OpenAlex

AbstractA half-century after the Cuban Missile Crisis, the world still overlooks the role played by U Thant—the quiet, unassuming UN secretary-general from Burma—in helping the superpowers resolve their crisis and avert nuclear war. Thant sent early and important messages to President John F. Kennedy and Soviet Premier Nikita Khrushchev. The first requested a moratorium on the conflict at sea. Although many of Kennedy's advisers looked upon Thant's initiative with derision, Kennedy asked Thant to send another message requesting a cessation of Soviet shipping. The message gave Khrushchev a way to stop his ships but still save face. This ended the threat of a naval confrontation and enabled the superpowers to focus on the deeper issues of the conflict. Early on, Thant also proposed and pushed the idea that eventually formed the basis of agreement: Soviet missile withdrawal in exchange for guarantees of Cuban security. During moments in the crisis when many were calling for an attack on Cuba, Kennedy and Secretary of State Dean Rusk cited Thant's initiatives as reasons for restraint. Thant also shuttled to Cuba to mollify Prime Minister Fidel Castro and to confirm that missile dismantlement had begun. He then aided the negotiations between Soviet and American teams at the United Nations to resolve remaining issues, such as how the missile withdrawal was to be verified.KeywordsCuban Missile CrisisKennedyKhrushchevnuclear warU ThantUnited Nations FundingThis research received funding from United Nations Studies at Yale University, and the authors thank Jim Sutterlin and Bruce Russett for their support in the initiation of this research. The authors also received research funds from the Canadian Aerospace Warfare Centre, which is gratefully acknowledged.Additional informationAuthor biographiesA. Walter Dorn is a professor of defence studies at the Royal Military College of Canada and chair of the department of security and international affairs at the Canadian Forces College.Robert Pauk is a retired Canadian military officer who served in UN peacekeeping operations.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.888
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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