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Record W3111241264 · doi:10.35297/qjae.010073

Austrian Economics and Organizational Entrepreneurship: A Typology

2020· article· en· W3111241264 on OpenAlexaff
Sara R. S. T. A. Elias, Todd H. Chiles, Qian Li, Fernando Antonio Monteiro Christoph D’Andrea

Bibliographic record

VenueThe Quarterly Journal of Austrian Economics · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTypologyEntrepreneurshipDisequilibriumAustrian SchoolSociologyEpistemologyPositive economicsPerspective (graphical)Punctuated equilibriumOrganizational studiesSocial scienceOrganizational learningPolitical scienceManagementNeoclassical economicsEconomicsLawAnthropology

Abstract

fetched live from OpenAlex

This article develops a typology for making sense of the numerous strands of Austrian (and Austrian-related) economics and demonstrates how this typology can guide organizational entrepreneurship scholars wishing to ground their research in Austrian thought. In the process, not only are existing insights from the history of Austrian economic thought rediscovered, but clearer light is also shed on important perspectives from that tradition that have received less attention in entrepreneurship research. Based on the Austrian concept of entrepreneurial production and its relationship with the core concepts of knowledge and change, the typology yields four perspectives—equilibration, punctuated equilibrium, disequilibration, and punctuated disequilibrium. These perspectives’ different paradigms as used in organizational research are explored, along with their ontological, epistemological, and methodological assumptions. The typology is illustrated with selected empirical examples from organizational research to spotlight the types of questions that contemporary scholars may appropriately ask and answer from each perspective.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.190
Teacher spread0.170 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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