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Record W2018144019 · doi:10.1177/0011392109104355

New Public Management and New Professionalism across Nations and Contexts

2009· article· en· W2018144019 on OpenAlexaffabout
Kevin T. Leicht, Tony Walter, Ivan Sainsaulieu, Scott Davies

Bibliographic record

VenueCurrent Sociology · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSalience (neuroscience)IdeologyAccountabilityPoliticsSociologyPublic administrationNew public managementPublic relationsNeoliberalism (international relations)Service delivery frameworkPublic servicePolitical sciencePublic sectorPolitical economyService (business)EconomicsEconomy

Abstract

fetched live from OpenAlex

The professions in the West are undergoing unprecedented calls for greater accountability and efficiency in service delivery. This article links these changes to recent developments in institutional theory that emphasize shifting salience of technical over symbolic organizational environments. The analysis of the adaptations to these changes in French and British healthcare, Canadian education and US managerial consulting suggest that country-specific responses to neoliberal institutional pressures are highly path dependent. The article concludes by suggesting a research program for the future study of the cross-national responses of professional groups to neoliberal economic and political ideologies.

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)0.004
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.025
Scholarly communication0.0090.007
Open science0.0000.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.065
GPT teacher head0.331
Teacher spread0.266 · 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

Citations107
Published2009
Admission routes2
Has abstractyes

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