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Record W3032041294 · doi:10.1177/0170840620934063

Speaking about vision, talking in the name of so much more: A methodological framework for ventriloquial analyses in organization studies

2020· article· en· W3032041294 on OpenAlexaff
Ellen Nathues, Mark van Vuuren, François Cooren

Bibliographic record

VenueOrganization Studies · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsVisionConceptualizationSociologyOrganization studiesTRACE (psycholinguistics)EpistemologyConstitutionPerspective (graphical)Order (exchange)Knowledge managementOrganizational communicationLinguisticsComputer scienceSocial sciencePolitical scienceBusinessLaw

Abstract

fetched live from OpenAlex

Organizations have long been treated as stable and fixed entities, defined by concrete buildings, catchy names, and strategic goals neatly written on paper. The Communicative Constitution of Organizations (CCO) school proposes an alternative, practice-grounded conceptualization for studying organizations as emerging in communicative (inter)actions. In so doing, CCO invites organizational scholars to trace back organizational phenomena to how they are communicated into existence. The concept of ventriloquism can help us explain the communicative constitutive view as it depicts how various elements of a situation are communicated into being and make a difference in interaction. However, ventriloquism lacks a proper methodological outline. Taking employee conversations about visions—a classic constituent of organizations—as our venue, we created a four-step framework for ventriloquial analyses and explored how visions are talked into existence. In this paper, we introduce and illustrate our analytical framework, showing how to identify, order, and present ventriloquial effects. We thus provide organizational (communication) scholars with a new methodological tool that facilitates the systematic inquiry into organizing and the organized from a communicative constitutive perspective.

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)0.001
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.200
GPT teacher head0.420
Teacher spread0.220 · 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 designObservational
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

Citations51
Published2020
Admission routes1
Has abstractyes

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