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Middle Managers, Strategic Sensemaking, and Discursive Competence

2010· article· en· W2110738270 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Management Studies · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsHEC Montréal
FundersEconomic and Social Research CouncilEngineering and Physical Sciences Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsSensemakingSituatedConversationMiddle managementSociocultural evolutionSociologyCompetence (human resources)LegitimationKnowledge managementPublic relationsPsychologyPolitical scienceComputer scienceSocial psychologyPoliticsCommunication

Abstract

fetched live from OpenAlex

abstract This paper seeks to better understand the way middle managers contribute strategically to the development of an organization by examining how they enact the strategic roles allocated to them, with particular reference to strategic change. Through vignettes drawn from the authors' current research, a framework is developed that shows two situated, but interlinked, discursive activities, ‘performing the conversation’ and ‘setting the scene’, to be critical to the accomplishment of middle manager sensemaking. Language use is key, but needs to be combined with an ability to devise a setting in which to perform the language. The paper shows how middle managers knowledgeably enact these two sets of discursive activities by drawing on contextually relevant verbal, symbolic, and sociocultural systems, to allow them to draw people from different organizational levels into the change as they go about their day‐to‐day work.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.248
Teacher spread0.213 · 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