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Record W2501706648 · doi:10.1177/0020852316655522

Strategic management in public administrations: a results-based approach to strategic public management

2016· article· en· W2501706648 on OpenAlexaff
Bachir Mazouz, Anne Rousseau

Bibliographic record

VenueInternational Review of Administrative Sciences · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsÉcole Nationale d'Administration Publique
FundersLuxembourg Institute of Science and Technology
KeywordsPublic managementNew public managementProcess (computing)Public relationsStrategic managementBusinessPublic administrationAction (physics)Field (mathematics)State (computer science)Political sciencePublic sectorMarketingComputer science

Abstract

fetched live from OpenAlex

As a field of knowledge, strategy has been taught and practised for over half a century. However, there is still a distinct lack of consensus surrounding the effectiveness of strategy in public administrations. This thematic issue of the International Review of Administrative Sciences is devoted to advanced research which claims that in the age of results-based management, public leaders must opt for a process-based approach to strategy. In doing so, the emphasis is put on the complexity of strategic processes that make it possible to support and maintain the institutions that serve the common good and the general interest and that deliver public services using the results of public action. From a process-based point of view, the strategy of public administration then assumes that analysts and public leaders need to be more aware of the specificities of state institutions. In particular, a thorough knowledge of the ways in which public officials interact with the fundamental values, structures, regulatory frameworks and administrative tools of public administrations is necessary.

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)0.006
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 score0.982
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.381
GPT teacher head0.498
Teacher spread0.117 · 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
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

Citations25
Published2016
Admission routes1
Has abstractyes

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