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Record W3170364941 · doi:10.11610/isij.4805

Multinational Cooperation and Intervention: Small Steps to Better Results

2021· article· en· W3170364941 on OpenAlexaff
Timothy H. Parsons, James J. Nolan, Frank Crispino

Bibliographic record

VenueInformation & Security An International Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsMultinational corporationIntervention (counseling)Psychological interventionPolitical scienceInternational communityHumanitarian interventionPeacekeepingAl qaedaDevelopment economicsTerrorismPsychologyPublic administrationLawInternational lawPoliticsEconomics

Abstract

fetched live from OpenAlex

This article considers the political and practical challenges inherent in large-scale multinational interventions executed by western powers, aimed at addressing regional instability through the application of military power to provide or restore local security.Reflecting upon recent well-publicised instances of such interventions, some of which have delivered otiose and often disappointing outcomes, it explores the efficacy of more limited interventions targeted at very specific problems.The authors argue in favour of a different style of security intervention: tightly focused, developed locally, delivered in partnership with community stakeholders and elected representatives -an approach that is reliant upon the contribution made by expert practitioners drawn from a range of contributing nations.This style of intervention remains vulnerable to external interference and malign political influence.Nevertheless, it is a model of international cooperation tested and proven to work if a conducive environment for implementation is established with support from inter-governmental organisations.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.004
Open science0.0000.000
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 head0.016
GPT teacher head0.316
Teacher spread0.300 · 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.

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
Published2021
Admission routes1
Has abstractyes

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