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Most cited business ethics publications: mapping the intellectual structure of business ethics studies in 2001–2008

2012· article· en· W2146925683 on OpenAlexaff
Zhenzhong Ma, Dapeng Liang, Kuo‐Hsun Yu, Yender Lee

Bibliographic record

VenueBusiness Ethics A European Review · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBusiness ethicsInformation ethicsStakeholderCorporate social responsibilityCitationResearch ethicsMoralityEngineering ethicsPhilosophy of businessApplied ethicsMeta-ethicsSociologyKnowledge managementPublic relationsBusinessPolitical scienceBusiness modelMarketingComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

This study explores the research paradigms of contemporary business ethics research in 2001–2008. With citation data from the top two business ethics journals included in the Social Sciences Citation Index, this study conducts citation and co‐citation analysis to identify the most important publications, scholars, and research themes in the business ethics area and then maps the intellectual structure of business ethics studies between 2001 and 2008. The results show that current business ethics studies cluster around four major research themes, including morality and social contract theory, ethical decision making, corporate social responsibility, and stakeholder theory. This study helps profile the invisible network of knowledge production in business ethics and provides important insights on current research paradigms of business ethics studies.

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)0.009
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.096
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0990.138
Science and technology studies0.0020.002
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.711
GPT teacher head0.490
Teacher spread0.221 · 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.

Study designObservational
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

Citations66
Published2012
Admission routes1
Has abstractyes

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