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Epistemic Community or Tower of Babel? Theoretical Diffusion in Public Administration

2008· article· en· W2054259996 on OpenAlexaboutno aff
Gaylord George Candler

Bibliographic record

VenueAustralian Journal of Public Administration · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsTower of BabelAdministration (probate law)Context (archaeology)Epistemic communityPublic administrationIvory towerPolitical scienceAcademic communitySociologySocial scienceLawHistoryPolitics

Abstract

fetched live from OpenAlex

This article takes a comparative look at the development of the public administration discipline in three countries: Australia, Brazil and Canada. The nature of the international public administration academic community is assessed through content analysis of articles in the Australian Journal of Public Administration (AJPA), Revista de Administração Pública (RAP), and Canadian Public Administration (CPA). The method is based on that used by existing United States (US) research, allowing for comparison with that national context. The focus is on the diffusion of theoretical approaches between these national contexts, assessing whether the international public administration discipline better approximates an epistemic community, in which theoretical approaches move seamlessly between the national contexts; or a ‘Tower of Babel’, in which the different national contexts remain largely isolated.

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)0.041
metaresearch head score (Gemma)0.097
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: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.007
Science and technology studies0.0080.049
Scholarly communication0.0170.037
Open science0.0020.016
Research integrity0.0030.004
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 head0.180
GPT teacher head0.418
Teacher spread0.238 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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