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Record W1855468808 · doi:10.1002/smj.2456

Video methods in strategy research: Focusing on embodied cognition

2015· article· en· W1855468808 on OpenAlexafffund
Philip Gylfe, Henrika Franck, Curtis LeBaron, Saku Mantere

Bibliographic record

VenueStrategic Management Journal · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMcGill University
FundersAalto-YliopistoMcGill University
KeywordsEmbodied cognitionCognitionAgency (philosophy)Middle managementPsychologyStrategic planningEmotional laborBridging (networking)Strategy implementationKnowledge managementComputer scienceCognitive psychologyBusinessSociologyMarketingSocial psychology

Abstract

fetched live from OpenAlex

Research summary : Video‐based methods can help researchers explore the significance of the human body in the practice of organizational strategy. We present a toolkit for the analysis of video data. The toolkit consists of three techniques: the detailing of significant forms in visual data, the sequencing of movement around such forms, and the patterning of movements across episodes. We employ these techniques on video recordings of middle managers engaged in a large‐scale strategic change effort. By revealing and analyzing the practices of “top‐down” and “bottom‐up bridging,” we show how the embodied cognition of middle managers supports strategy implementation by influencing nascent behavioral and cognitive changes among their subordinates. We conclude our account by suggesting a research agenda for video‐based work in strategy research . Managerial summary : We explore video-based methods as a means to understand how middle managers incorporate strategic change in their practice. During strategic change efforts, a lot of what is taken to be the buildup of “shared understanding” is more appropriately viewed as emotional contagion. The success of middle management change agency is thus measured, not only by their successful elaboration of strategy content to others, but also whether or not organizational members invest themselves emotionally to the change endeavor. Such contagion is founded on the interaction of human bodies as well as their verbal discourse . Copyright © 2015 John Wiley & Sons, Ltd.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.291
GPT teacher head0.408
Teacher spread0.117 · 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.

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

Citations113
Published2015
Admission routes2
Has abstractyes

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