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Record W2606242408 · doi:10.1177/030630700803300305

Juggling Janus – Strategy for General Managers in an Age of Paradoxical Trends

2008· article· en· W2606242408 on OpenAlexaff
Leyland Pitt, Bodo B. Schlegelmilch

Bibliographic record

VenueJournal of General Management · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGloomProsperityFace (sociological concept)Balance (ability)Power (physics)PopulationJanusBLISSDevelopment economicsPolitical economyEconomicsPolitical scienceSociologySocial scienceEconomic growthPsychologyDemography

Abstract

fetched live from OpenAlex

Whereas trends in the modern age tended to be linear and unidirectional, the trends in our postmodern times are more likely to be paradoxical. Like the Roman god Janus, they have two faces, and are seldom simply positive or negative, or universally ‘good’ or ‘bad’. This article identifies and describes eight such trends, and looks at each of their ‘faces’. The trends include the growth in prosperity, free markets, population growth, global bliss and gloom, the power of multinationals, worldwide media reach, the age of brands, and the decline of service. We argue that simple applications of strategy might be inappropriate in the face of these paradoxical trends, and that firms will have to consider revolutionary changes to strategy in order to achieve strategic balance.

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)0.008
metaresearch head score (Gemma)0.010
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 score0.015
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.020
Scholarly communication0.0150.015
Open science0.0010.005
Research integrity0.0030.004
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 head0.059
GPT teacher head0.277
Teacher spread0.218 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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