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“Modernizing Government”: Mapping Global Public Policy Networks

2011· article· en· W1946339087 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGovernance · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsCarleton UniversityUniversity of Regina
FundersInternational Labour Organization
KeywordsRestructuringGovernment (linguistics)HyperlinkGlobalizationPublic policyThe InternetPublic administrationBusinessPublic relationsEconomicsPolitical scienceEconomic growthFinanceMarket economyWeb pageComputer science

Abstract

fetched live from OpenAlex

Public sector reform is a key policy area, driven by global public policy networks. Research on these networks has been inductive, highlighting organizations like the Organisation for Economic Co-operation and Development (OECD). This article examines “virtual policy networks” (VPNs) on the Web. Using IssueCrawler, we conduct a hyperlink analysis that permits us to map seven VPNs. The first network mapped the hyperlinks of 91 organizations identified through inductive methods. The hypothesis that the virtual network would include all actors identified in the inductive approach was refuted. The other six networks focused on: market mechanisms, open government, performance, public employment, reform, and restructuring. Among the findings, the U.S. government is prominent in the first three, while international organizations dominate the others. VPN rankings show that the World Bank dominates the OECD. When the inductive research is blended with the VPN research, the OECD's prominence increases, and we see the importance of market mechanisms and reform VPNs as pillars of globalization.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.117
GPT teacher head0.353
Teacher spread0.235 · 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