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To the issue of the formation of peacekeeping idea (on the example of the Suez Crisis of 1956)

2020· article· en· W3009782089 on OpenAlexaboutno aff
Dar'ya Mikhailovna Pokrovskaya

Bibliographic record

VenueTambov University Review Series Humanities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsnot available
Fundersnot available
KeywordsPeacekeepingSettlement (finance)Conflict resolutionPolitical scienceVetoLawPolitical economySociologyPoliticsBusiness

Abstract

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The Suez Crisis of 1956 is considered one of the most acute regional conflicts of the Cold War period. Two of the five member states of the Security Council were involved in the conflict, who actively exercised the right of “veto” during any attempts at settlement, which paralyzed the existing mechanism for resolving conflicts within the UN. The disagreements of the “great” powers threatened to grow from a diplomatic confrontation into a military one, and conflict from regional to global. The solution was found at one of the sessions of the General Assembly, where Canadian L.B. Pearson presented his idea of resolving the conflict by creating the UN Emergency Forces. The study is devoted to the idea of creating a UN peacekeeping force, the founder of which is Canadian diplomat L.B. Pearson. The purpose of this study is to analyze the role of L.B. Pearson in the formation of the idea of peacekeeping, on the example of participation in the settlement of the Suez Crisis. We discuss the historical aspects and conditions for the creation of the UN Emergency Forces, a comparative analysis was conducted with the first observation missions of the UN, substantiate principles, which became the basis for the functioning of peacekeeping forces. We draw conclusion that it was L.B. Pearson’s ideas that contributed to the resolution of one of the most acute crises of the second half of the 20th century, and the creation of peacekeeping forces proved the effectiveness of the UN in maintaining international peace and security, conflict resolution, and also laid the foundation for modern peacekeeping.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.068
GPT teacher head0.264
Teacher spread0.196 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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