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Record W2460339334 · doi:10.1177/1056492616656407

Quantum Sustainable Organizing Theory

2016· article· en· W2460339334 on OpenAlexaff
Bruno Dyck, Nathan Greidanus

Bibliographic record

VenueJournal of Management Inquiry · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndeterminismQuantum entanglementEpistemologyQuantumSociologyQuantum mechanicsPhysicsDeterminismPhilosophy

Abstract

fetched live from OpenAlex

We draw on quantum physics ideas of “entanglement” and “indeterminism” to introduce and develop “Quantum Sustainable Organizing Theory” (QSOT). Quantum entanglement points to the interconnectedness of matter in ways that defy Newtonian physics and commonsense assumptions that underlay conventional organizing theory. Quantum indeterminism suggests that uncertainty is an inherent feature of reality and not simply a lack of information that impedes rational decision making. Taken together, these quantum ideas challenge the assumptions of conventional organizational theorizing about the boundaries between a firm and its natural and social environment, the importance of self-interested individualism and (sociomaterial) financial measures of performance, the emphasis on competitiveness, and the hallmarks of rational theory and practice. We discuss implications for sustainable organizing in particular and for organization theory more generally.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.230
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

Citations24
Published2016
Admission routes1
Has abstractyes

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