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Record W2803371979 · doi:10.1007/s40901-018-0084-9

The Security Council veto and Syria: responding to mass atrocities through the “Uniting for Peace” resolution

2017· article· en· W2803371979 on OpenAlexfundno aff
Graham Melling, Anne Dennett

Bibliographic record

VenueIndian Journal of International Law · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
FundersYork UniversityStrong
KeywordsVetoLegitimacyCharterPolitical scienceSecurity councilResponsibility to protectLawCredibilityPublic administrationInternational lawPolitics

Abstract

fetched live from OpenAlex

The Syrian conflict has brought into sharp focus the exercise of the veto by some permanent members of the Security Council, highlighting significant shortcomings in the Council’s ability to respond effectively to grave humanitarian situations, particularly those involving mass atrocity crimes. It has also raised issues of legitimacy and credibility in Security Council decision-making, yet a growing clamour within the General Assembly for veto reform has, to date, not resulted in tangible change. The purpose of this article is to examine how the Security Council can improve the effectiveness of its response to humanitarian concerns but still maintain its position at the centre of the response to threats to international peace and security. We explore whether the Uniting for Peace Resolution can provide a constitutional response to negating the exigencies of the veto and enhance legitimacy in Security Council decision-making whilst keeping the Security Council at the centre of the solution. As a practical remedy to unblocking the Security Council in limited circumstances, we advocate an approach which maintains the constitutional balance of power under the United Nations Charter by placing the Security Council, as the body tasked with primary responsibility for the maintenance of international peace and security, at the centre of the operation of the Uniting for Peace Resolution by determining when its use is appropriate and what measures will be adopted as a consequence. We propose the use of independent monitoring and verification bodies to carry out fact-finding and objective evaluation to strengthen the legitimacy of Uniting for Peace.

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)0.016
metaresearch head score (Gemma)0.022
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.020
Scholarly communication0.0160.007
Open science0.0010.009
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.042
GPT teacher head0.331
Teacher spread0.289 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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