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Record W3092208770 · doi:10.1007/s11558-020-09403-z

Intervention by international organizations in regime complexes

2020· article· en· W3092208770 on OpenAlexaff
Matias E. Margulis

Bibliographic record

VenueThe Review of International Organizations · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntervention (counseling)BureaucracyPoliticsCompetition (biology)Political scienceFood securityControl (management)Public relationsLaw and economicsPublic administrationAgricultureSociologyLawEconomicsPsychologyManagement

Abstract

fetched live from OpenAlex

Abstract This article identifies the existence of a previously unknown but important type of self-directed political behavior by International Organizations (IOs) that I term intervention . Intervention occurs when an IO secretariat acts with the intention of altering an anticipated decision at a partially-overlapping IO in a regime complex. Intervention is a distinct type of behavior by IOs that differs from either bureaucratic competition among IOs for mandates, resources and policy influence, or cooperation to achieve joint regulatory goals and enhance performance. I probe the plausibility of intervention through an analysis of three illustrative case studies in the regime complex for food security showing self-directed political actions by the secretariats of the Food and Agriculture Organization (FAO), World Food Programme (WFP) and Office of the High Commissioner for Human Rights (OHCHR) directed at altering decision-making by states at the World Trade Organization (WTO). I identify three distinct intervention strategies – mobilizing states, public shaming and invoking alternative legal frameworks – in which IOs utilize their material, ideational and symbolic capabilities to influence decision-making not within their own institutions, but at other, overlapping organizations in a regime complex over which they have no direct control.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.313
Teacher spread0.297 · 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

Citations37
Published2020
Admission routes1
Has abstractyes

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