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Record W3088683451 · doi:10.1093/jogss/ogaa043

The Gray Area of Institutional Change: How the Security Council Transforms Its Practices on the Fly

2020· article· en· W3088683451 on OpenAlexaff
Vincent Pouliot

Bibliographic record

VenueJournal of Global Security Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsMcGill University
Fundersnot available
KeywordsFormalityCorporate governancePoliticsPolitical scienceCharterCasualGray (unit)Public relationsInterdependencePublic administrationManagementLawEconomics

Abstract

fetched live from OpenAlex

Abstract In world politics, institutional development often takes place in a gray area that combines elements of rational design and organic change in practice. Faced with impracticable secondary rules, diplomats evolve semi-formal practices that allow them to make collectively binding decisions even in the absence of a procedure to do so, effectively building the plane while flying it. Changing practices at the United Nations Security Council offer a particularly significant and fertile case here. The ways in which the body conducts its business have significantly evolved in the post–Cold War era, though in the absence of formal changes to the Charter or the Council's Rules of Procedure. How is such a casual institutional transformation possible in the most politicized global governance body? Building on practitioners’ accounts, the article maps out the four spaces of semi-formality and the attendant practices by which the Council transforms itself. First, Council diplomats value flexibility and allow each other to innovate. Second, they attempt to codify evolving ways of conducting Council business. Third, a set of training practices allows for socialization in ways of doing things. Fourth and finally, diplomats on the Council have limited opportunities to collectively discuss their changing practices. Overall, the article suggests that gray zones are far more pervasive than currently acknowledged in world politics, calling for more scholarly interest in this hybrid mode of institutional change in which design emerges organically and is collectively owned.

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)0.024
metaresearch head score (Gemma)0.026
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 score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.071
Scholarly communication0.0170.010
Open science0.0020.014
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.254
GPT teacher head0.386
Teacher spread0.132 · 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

Citations58
Published2020
Admission routes1
Has abstractyes

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