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Record W1579835596

Building the New Managerialist State: Consultants and the Politics of Public Sector Reform in Comparative Perspective

2004· book· en· W1579835596 on OpenAlexaboutno aff
Denis Saint‐Martin

Bibliographic record

VenueOUP Catalogue · 2004
Typebook
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsManagerialismStatismPoliticsPublic administrationState (computer science)Government (linguistics)Political sciencePerspective (graphical)Public sectorNew public managementManagementSociologyLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

In the 1980s and 1990s the world of governance witnessed a far-reaching change from the Weberian model of bureaucracy to the 'new managerialism'-a term used to describe the group of ideas imported from business and mainly brought into government by management consultants. Over the past fifteen years, the British, French, and Canadian governments have spent growing sums of money on consulting services and, as a result, policy-makers inside the state have increasingly been exposed to the business management ideas that consultants bring into the public sector. Nevertheless, there are major differences in the extent to which reformers in the three countries embraced these ideas in the process of bureaucratic reform. Accordingly, this is a book about policy change and variation. It seeks to explain why the changes produced by the new managerialism have been more radical in some countries than in others. Building the New Managerialist State shows that the reception given by states to managerialist ideas depends on the openness of policy-making institutions to outside expert knowledge and on the organization, development, and social recognition of management consultancy.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.015
Scholarly communication0.0100.007
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.313
Teacher spread0.275 · 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 designNot applicable
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

Citations135
Published2004
Admission routes1
Has abstractyes

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