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Record W2111624246 · doi:10.1111/1467-8551.00225

The Conventions of Management Research and their Relevance to Management Practice

2002· article· en· W2111624246 on OpenAlexaff
Mihaela Kelemen, Pratima Bansal

Bibliographic record

VenueBritish Journal of Management · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsJargonRelevance (law)Context (archaeology)Practitioner researchPublic relationsMode (computer interface)PsychologySociologyKnowledge managementEngineering ethicsPolitical scienceComputer sciencePedagogyEngineeringLinguistics

Abstract

fetched live from OpenAlex

This paper recognizes the failure of management research to communicate with practitioners, and speculates over the reasons why this may be the case. It is possible that the researchers’ interests may not always coincide with management practitioners’; however, even when such interests are congruent, it seems that relatively little management research is published in practitioner journals. We suggest that this is because academic research is written in a style that tends to alienate most practitioners. This paper isolates the stylistic conventions associated with research targeted to academics (typically published in academic journals) and research targeted to practitioners (typically published in practitioner‐oriented journals). Such stylistic differences are illustrated through a study of organizational change whose findings have been published in both academic and practitioner format, namely in the Administrative Science Quarterly and the Harvard Business Review. We suggest that the gap between these two types of research could be narrowed through processes of translation (i.e. academic jargon could be translated in practitioner language). In addition we might consider greater use of Mode 2 research over Mode 1 research (academic). Mode 2 research presupposes that teams of academics and practitioners assemble to define the research problem and methodology in terms appropriate to a particular context and in a way that accounts for all existing interests so that translation processes are seamless. However, Mode 2 creates its own gap in that the knowledge is more contextual and may not reach a wide audience.

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)0.172
metaresearch head score (Gemma)0.287
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.910

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1720.287
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.012
Science and technology studies0.0100.139
Scholarly communication0.0400.024
Open science0.0040.014
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0020.002

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 head0.037
GPT teacher head0.271
Teacher spread0.235 · 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 designTheoretical or conceptual
DomainMethods
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

Citations13
Published2002
Admission routes1
Has abstractyes

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