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Record W3014219573 · doi:10.1177/0010836720906191

When democratic governance unites and divides: Social status and contestation in the Organization for Security and Co-operation in Europe

2020· article· en· W3014219573 on OpenAlexfundno aff
Catherine Hecht

Bibliographic record

VenueCooperation and Conflict · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsnot available
FundersUniversität Duisburg-EssenSocial Sciences and Humanities Research Council of CanadaCentre for Global Cooperation ResearchUniversität Wien
KeywordsScholarshipPolitical sciencePolitical economyCorporate governancePoliticsSociologyState (computer science)Social orderDiplomacyDemocracyPublic administrationLaw

Abstract

fetched live from OpenAlex

Scholars and practitioners are increasingly attentive to contestation against symbols and institutions underpinning international order(s). Yet International Relations scholarship can benefit from greater understanding of ways in which contestation interacts with salient dimensions of social status in specific international organizations (IOs). Drawing on evidence from the history of the Organization for Security and Co-operation in Europe (OSCE), with a focus on democratic governance and human rights, this article analyzes status-related contestation as a significant, yet under-examined type of contestation in multilateral diplomacy. Status-related contestation conveys dissatisfaction about symbols, institutions, and actors which reinforce socially significant divisions that place a state (or group of states) at a social disadvantage in a particular multilateral venue. International organizations provide unique social contexts which affect the content of contestation. Building on scholarship in social psychology, constructivism, and status hierarchies in world politics, the article analyzes the evolution of a dimension (or basis) of social status in the OSCE and illustrates that, beyond domestic and material interests, state representatives communicate social identity-related concerns through language, for example, that expresses discontent with dividing lines, unfairness, or (dis)respect, in attempting to minimize negative social identities in multilateral organizations.

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)0.012
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: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0090.031
Scholarly communication0.0140.008
Open science0.0010.009
Research integrity0.0020.002
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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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