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Record W1975845590 · doi:10.1177/0011392108093832

Governing through Global Networks

2008· article· en· W1975845590 on OpenAlexaff
Suzan Ilcan, Lynne Phillips

Bibliographic record

VenueCurrent Sociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsGovernmentalityField (mathematics)SociologyGlobal networkWork (physics)Citizen journalismGovernment (linguistics)Space (punctuation)Participatory developmentPublic relationsActor–network theoryKnowledge managementPolitical scienceSocial scienceComputer scienceLawPoliticsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This article moves beyond the `network society' thesis to provide an analysis of select global organizations and their global knowledge networks in the field of development. Drawing on the work of contemporary theorists of governmentality, the authors argue that global knowledge networks facilitate the movement of knowledge across space and time, and adjoin particular principles as a means of governing. These networks operate as mobile technologies of government, and seek to manage the objects of development, prescribe proper conduct and cultivate active agents and citizens through participatory development activities. The authors' claims are based on extensive policy documents, reports, network-based development programmes affiliated with specific global organizations and interviews conducted with United Nations policy and research personnel.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0080.013
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.084
GPT teacher head0.387
Teacher spread0.303 · 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 designTheoretical or conceptual
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

Citations32
Published2008
Admission routes1
Has abstractyes

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