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Record W1909498465 · doi:10.1177/1548051815598007

From Stories to Schemas

2015· article· en· W1909498465 on OpenAlexaff
Robert Steinbauer, Nicholas D. Rhew, H. Shawna Chen

Bibliographic record

VenueJournal of Leadership & Organizational Studies · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsLaurentian UniversityBrock University
Fundersnot available
KeywordsSensemakingDynamismFace (sociological concept)Process (computing)Meaning (existential)Dual (grammatical number)Focus (optics)EpistemologyScholarshipPsychologyMeaning-makingComputer scienceCognitionSociologyCognitive scienceKnowledge managementPolitical science

Abstract

fetched live from OpenAlex

Today’s leaders face unprecedented complexity and dynamism in the external environment. Sensemaking provides a useful framework for understanding how leaders extract meaning from that environment; however, its focus on purely conscious processes limits its applicability. We revisit and overcome major epistemological and ontological arguments against reconciling sensemaking with other decision-making models. This allows us to propose a dual systems model of sensemaking by introducing unconscious sensemaking as a complementary process that supports conscious sensemaking. We propose that the plausible stories that result from conscious sensemaking lead to schemas over time through which leaders can unconsciously make sense of their environment. This dual systems model holds important implications for leadership scholarship, in both describing leaders’ cognitive processes and how those leaders can utilize this improved model to better effect change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.169
GPT teacher head0.293
Teacher spread0.125 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations11
Published2015
Admission routes1
Has abstractyes

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