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Record W2196528696 · doi:10.5539/ibr.v9n1p123

Myths and Narratives for Management

2015· article· en· W2196528696 on OpenAlexvenueno aff
Ulrich Gehmann

Bibliographic record

VenueInternational Business Research · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)Set (abstract data type)ObjectificationNarrativeFunction (biology)EpistemologyMythologyProcess (computing)SociologyDisk formattingPsychologyAestheticsComputer scienceLinguisticsPhilosophyLiteratureArtMathematics

Abstract

fetched live from OpenAlex

Having in mind the social, human, cultural and systemic problems management is confronted with today, but also the intricate relationships between art and technique, the recent predominant understanding of what ‘management’ is settles upon its technical, that is, essentially functional character. The thesis is that this basic character has not changed, despite all attempts to redefine, modify, or even re-think management as a cultural practice. Related to this basic character, some elements of the mind set underlying such an understanding of ‘management’ shall be examined, elements which may be called mythic. For such a mind set, management is primarily conceived as a function, and as in case of every process that is technical in its essence, it finally aims at an objectification and optimization of the entities it has to deal with. That functional character, and out of it, the desire for dominating the respective entities by formatting them rests on certain assumptions about a ‘relevant’ world, assumptions to be examined in this contribution.

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)0.010
metaresearch head score (Gemma)0.012
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: none
Teacher disagreement score0.018
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0130.067
Scholarly communication0.0180.020
Open science0.0020.008
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0060.001

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 head0.103
GPT teacher head0.359
Teacher spread0.256 · 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

Citations31
Published2015
Admission routes1
Has abstractyes

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