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The Changing Nature of Public Entrepreneurship

2007· article· en· W2150244412 on OpenAlexaffabout
Luc Bernier, Taı̈eb Hafsi

Bibliographic record

VenuePublic Administration Review · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsHEC MontréalÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsEntrepreneurshipGovernment (linguistics)Control (management)Public policyPublic relationsSociologyBusinessEconomicsPolitical scienceManagementEconomic growthFinance

Abstract

fetched live from OpenAlex

This article proposes a cyclical theory of public entrepreneurship that is rooted in contextual conditions. The authors use material presented to the Institute of Public Administration of Canada for the annual innovation award, as well as an extensive literature review, to illustrate a new model for public entrepreneurship, arguing that today’s public entrepreneurs are teams and their actions are systemic. Public entrepreneurs do not create new artifacts, nor do they design grandiose projects, but they slowly reinvent their organizations and, in so doing, transform the systems that control government effectiveness and efficiency. The authors generalize and contextualize the idea of public entrepreneurship and structure the emergence of entrepreneurs into a cycle theory. The individual entrepreneur dominates when the organization is new or there is a need for novel activities. As the organization matures and the need for efficiency takes over, dominant individual entrepreneurship disappears, and with time, a new systemic entrepreneurship arises to tackle them.

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)0.009
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 score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.008
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.293
Teacher spread0.257 · 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

Citations271
Published2007
Admission routes2
Has abstractyes

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