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Record W1966823729 · doi:10.1177/1056492612458453

Refining, Reinforcing and Reimagining Universal and Indigenous Theory Development in International Management

2012· article· en· W1966823729 on OpenAlexaff
Gavin Jack, Yunxia Zhu, Jay B. Barney, Mary Yoko Brannen, Craig Prichard, Kulwant Singh, David A. Whetten

Bibliographic record

VenueJournal of Management Inquiry · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal and Cross-Cultural Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsScholarshipViewpointsSociologyIndigenousContext (archaeology)Perspective (graphical)EpistemologyDevelopment theoryEngineering ethicsPolitical scienceLawEconomic growthComputer scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

This article addresses a long-established yet still contentious question in international management scholarship—Is it possible and desirable to create a universal theory of management and organization? Scholarship about the boundary conditions of endogenous theory and the need for indigenous theories of management as well as geopolitical changes in the world order have animated this debate. Five leading scholars discussed this topic at a symposium held at the 2009 Academy of Management meeting. This article presents an analysis of their viewpoints. Three key perspectives were identified in the debate: the refining perspective, the reinforcing perspective, and the reimagining perspective. Using excerpts from the symposium transcript, we outline, compare, and critically evaluate the characteristics and significance of each perspective to advancing theory development. The distinctive contribution of this article lies in its meta-theoretical debate about the relationship between theory, context, and power in the production of global management knowledge.

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)0.035
metaresearch head score (Gemma)0.021
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 score0.035
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0060.059
Scholarly communication0.0110.016
Open science0.0020.008
Research integrity0.0020.005
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 head0.027
GPT teacher head0.310
Teacher spread0.282 · 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

Citations61
Published2012
Admission routes1
Has abstractyes

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