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Re-conceptualizing Vision at the Intersection of Leadership and Strategic Management

2018· article· en· W2834240370 on OpenAlexaff
Kim Myrick, E. Kevin Kelloway

Bibliographic record

VenueAcademy of Management Proceedings · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsConceptualizationStrategic planningIntersection (aeronautics)Strategic leadershipCraftSociologyKnowledge managementBusinessPolitical scienceComputer scienceEngineeringArtificial intelligenceMarketing

Abstract

fetched live from OpenAlex

An approach is developed to re-conceptualize “organizational vision” at the intersection of leadership and strategic management, defining vision as an affectively powered image of an organization with informative content on the ideal state of the organization. The theoretical conceptualization of vision and the effective use of it in organizational management may be held back by ways in which vision has been treated in the management literature. Drawing on the management literature in the areas of leadership and strategic management, definitions and characteristics of vision are reviewed and synthesized to inform further research on the concept. Propositions are developed that integrate the perspectives of leadership and strategic management on vision content. Direction is suggested for research on vision and vision creation as a manageable process. There are implications for organizations to craft vision statements that create stronger links between leadership and strategic management for the betterment of organizations and their stakeholders and society.

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)0.007
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 score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.004
Science and technology studies0.0040.022
Scholarly communication0.0110.020
Open science0.0020.006
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.061
GPT teacher head0.270
Teacher spread0.210 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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