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Record W2604589690 · doi:10.1177/0021886317697971

Aesthetic Rationality in Organizations: Toward Developing a Sensitivity for Sustainability

2017· article· en· W2604589690 on OpenAlexaff
Paul Shrivastava, Günter Schumacher, David M. Wasieleski, Marco Tasic

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsConcordia University
Fundersnot available
KeywordsRationalityValue (mathematics)SustainabilityVirtueSociologySustainable developmentEpistemologyKnowledge managementPsychologyComputer sciencePolitical sciencePhilosophyEcologyLaw

Abstract

fetched live from OpenAlex

This article explains the coexistence and interaction of aesthetic experience and moral value systems of decision makers in organizations. For this purpose, we develop the concept of “aesthetic rationality,” which is described as a type of value-oriented rationality that serves to encourage sustainable behavior in organizations, and to complete the commonly held, “instrumentally rational” view of organizations. We show that organizations regularly exhibit not only an instrumental rationality but also an “aesthetic rationality,” which is manifested in their products and processes. We describe aesthetics, its underlying moral values, its evolutionary roots, and its links to virtue ethics as a basis for defining the concept of aesthetic rationality. We examine its links with human resources, organizational design, and other organizational elements. We examine these implications, identify how an aesthetic-driven ethic provides a potential for sustainable behavior in organizations, and suggest new directions for organizational research.

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)0.008
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 score0.008
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.039
Scholarly communication0.0080.006
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.144
GPT teacher head0.376
Teacher spread0.232 · 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

Citations27
Published2017
Admission routes1
Has abstractyes

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