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Record W2486768049 · doi:10.1016/s0732-1317(06)15022-8

The Administrative State in a Globalizing World: Some Trends and Challenges

2006· book-chapter· en· W2486768049 on OpenAlexaboutno aff
Gerald E. Caiden

Bibliographic record

VenueResearch in public policy analysis and management · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal History, Politics, and Ideology
Canadian institutionsnot available
Fundersnot available
KeywordsGlobeHumanityGlobalizationPolitical scienceState (computer science)World orderQuarter (Canadian coin)Order (exchange)Human rightsPolitical economyLawHistorySociologyBusinessPsychologyComputer sciencePolitics

Abstract

fetched live from OpenAlex

For centuries, dreamers have looked forward to the day when people would overlook their differences and recognize all as brothers, that under their skin they were very much alike and aspired to much the same future. Then, they would see the advantages of cooperating together, burying their disagreements, and working toward common objectives. Barriers between people would be removed. People and goods would move freely across the globe. Every human being would be accorded the same rights and be treated with the same consideration. And people would lay down their arms and make peace, not war. The world would unite and all human beings would realize that they shared a common fate. In time, the advancement of technology has indeed reduced distance and increased mobility, thereby bringing people closer and closer together and uniting the planet. But the experience of global warfare in increasingly horrifying form has made imperative an end to the madness of continued internecine conflict and a need to create universal bonds. Slowly, in fits and starts, the world's statesmen began to devise a new international order that would better suit humanity until in the last quarter of the 20th century, the world awoke to the fact that the future had at last arrived at thanks to 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.

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)0.005
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.765
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.193
GPT teacher head0.435
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations14
Published2006
Admission routes1
Has abstractyes

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