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Record W2127893556

Narcissus Revisited: The Values of Management Academics and their Role in Business School Strategies in the UK and Canada

2004· article· en· W2127893556 on OpenAlexaboutno aff
David R. Stiles

Bibliographic record

VenueSSRN Electronic Journal · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetaphorIdentity (music)InstitutionValue (mathematics)SociologyPerspective (graphical)Set (abstract data type)Element (criminal law)Public relationsCreating shared valueMode (computer interface)Empirical researchManagementEpistemologyPolitical scienceSocial scienceLawAesthetics
DOInot available

Abstract

fetched live from OpenAlex

The myth of Narcissus provides an appropriate metaphor for the continuing debate over the relationship between academics, business and other stakeholders; most recently expressed in terms of Mode 1 and Mode 2 knowledge and academic entrepreneurialism. Both myth and debate are based partly on conflicts over identity. However, surprisingly little empirical work has been conducted on the identity of management academics. A step towards this is made here by exploring the role of embedded and enduring values as a primary element of academic identity in business schools. Contextualized in the Mode/entrepreneuralism debate, a layered metaphor of academic organization is adopted, in which values are located among deep-set constructs and a comparative and longitudinal perspective employed. A value-ranking instrument is devised, applied and retested over five years in two business schools in Britain and Canada. This reveals values that are widely held by management academics and those that are more pervasive in each institution. Understanding such values helps provide insight into the strategic role of academic identity, grounded in ontological and epistemological frameworks.

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)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0240.031
Scholarly communication0.0200.004
Open science0.0020.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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 designQualitative
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

Citations9
Published2004
Admission routes1
Has abstractyes

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