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Record W4407996141 · doi:10.1108/ejms-07-2024-0081

Advancing management scholarship internationally through theoretical emancipation

2025· article· en· W4407996141 on OpenAlexaff
Ke Cao, Tong Li, Yongzhi Du

Bibliographic record

VenueEuropean Journal of Management Studies · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsEmancipationScholarshipSociologyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Purpose An increasing consensus has been built on advancing management scholarship in contexts other than Anglophone North America. However, debates and arguments about how to do so remain, and there has not been a clear understanding of the progress made. This study aims to conduct a comprehensive and historical assessment of related scholarship and provide recommendations for the path forward. Design/methodology/approach Around 2,700 international context-based empirical papers published from 1990 to 2020 in 4 elite general management journals were reviewed. Other relevant publications on the margins and related academic discussions were also analyzed. Findings At elite outlets, international-context-based research is characterized by a gradual decrease in intellectual vigor and methodological variety, a disregard for context and indifference to practice. At outlets on the edge, research is less constrained by dominant and rigid academic discourse. Research limitations/implications The paper prioritizes liberatory thinking about theoretical contribution as the key solution for the academic impasse. Extant theories shall be conceptualized as context-bounded heuristics rather than universal truths. Additional provocations and suggestions about reforming research practice were provided. Originality/value The study is the first comprehensive literature survey in this area. Meanwhile, new, grounded and provocative recommendations have been outlined for a bold and robust reset of academic discourse.

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)0.002
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: none
Teacher disagreement score0.958
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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