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Record W2344108343

The role of verification in international relations: 1945-1993

2006· dissertation· en· W2344108343 on OpenAlexfundno aff

Bibliographic record

VenueCommon Library Network (Der Gemeinsame Bibliotheksverbund) · 2006
Typedissertation
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryInstitute on Global Conflict and Cooperation, University of California, San DiegoNational Center for PTSD, U.S. Department of Veterans AffairsHarvard Kennedy SchoolWestfälische Wilhelms-Universität MünsterCenter for International Security and Cooperation, Stanford UniversityEidgenössische Technische Hochschule ZürichMoscow Institute of Physics and TechnologyInternational Institute for Applied Systems AnalysisInstitut für WeltwirtschaftOpen Society InstituteFreie Universität BerlinSan Diego Supercomputer CenterUniversität SalzburgLatvijas UniversitateMcMaster UniversityKing's College LondonGeorge Washington UniversityInfectious Diseases Society of AmericaJames Madison UniversityJohns Hopkins UniversityBelfer Center for Science and International Affairs, Harvard UniversityCenter for Global PartnershipHarvard UniversityHumboldt-Universität zu BerlinUniversität HamburgU.S. Army
KeywordsNegotiationInternational relationsPolitical sciencePoliticsManagement scienceComputer scienceEngineering ethicsPublic relationsEpistemologyEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

The role of verification in international relations is liked with the urge to verify which is evident throughout human history. This study focused on the evolution of this role in light of political circumstances and technological progress. Several different approaches to verification can be identified – bilateral, regional cooperation, global arrangements, and individual national efforts. Moreover, several themes characterize the existing verification regimes. These issues – namely the sharing of intelligence, managing compliance questions, and the integration of different regimes – present themselves as the negotiating ground for future years. One of the important result of the paper is that it demonstrates how the concept of verification, once a contentious political instrument, is encompassing anew actors, new frameworks, new technologies, and new fields.

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)0.008
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0070.023
Scholarly communication0.0110.013
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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 designQualitative
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

Citations1
Published2006
Admission routes1
Has abstractyes

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