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Record W2340613512 · doi:10.1177/0018726715624497

Commentary: Beyond Morgan’s eight metaphors

2016· article· en· W2340613512 on OpenAlexaff
Gareth Morgan

Bibliographic record

VenueHuman Relations · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsYork University
Fundersnot available
KeywordsMetaphorFace (sociological concept)EpistemologySociologyProcess (computing)GRASPMetonymyPoliticsOrganizational theoryMetaphor and metonymyCognitive sciencePsychologySocial scienceComputer sciencePolitical scienceLinguisticsManagement

Abstract

fetched live from OpenAlex

This article focuses on the interplay between metaphor and metonymy in the construction of organization theory. It emphasizes the importance of understanding the relationship between the use of metaphor as a way of thinking and a way of being, and the specific metaphors that are produced through this process. It suggests that too much emphasis is often placed on metaphors as abstracted epistemological constructs rather than on understanding the more dynamic and changing role they play in the interactive modes of engagement through which people seek to grasp, concretize and act on their world. Developing the approach and ideas first presented in Images of Organization, this article suggests that a flexible use of metaphor can help us engage and understand the multidimensional and paradoxical nature of organizational life and help us to deal with the emerging issues shaping the contemporary socio-political–technological–organizational landscape. The article suggests that because most current approaches in social science are overly-focused on the study of abstracted metonymical constructs, they will have difficulty dealing with the multidimensional complexity we now face.

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)0.007
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.039
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.013
Scholarly communication0.0050.011
Open science0.0060.004
Research integrity0.0390.059
Insufficient payload (model declined to judge)0.0070.004

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations52
Published2016
Admission routes1
Has abstractyes

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