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Record W2152664775 · doi:10.1177/2041386613489062

Sensemaking and emotion in organizations

2013· article· en· W2152664775 on OpenAlex
Sally Maitlis, Timothy J. Vogus, Thomas B. Lawrence

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.

Bibliographic record

VenueOrganizational Psychology Review · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsSensemakingPsychologyProcess (computing)Social psychologyEmotion workInterpersonal communicationCognitive psychologyKnowledge managementComputer science

Abstract

fetched live from OpenAlex

Emotion is a critical but relatively unexplored dimension of sensemaking in organizations. Existing models of sensemaking tend to ignore the role of emotion or portray it as an impediment. To address this problem, we explore the role that felt emotion plays in three stages of individual sensemaking in organizations. First, we examine emotion’s role in mediating the relationship between unexpected events and the onset of sensemaking processes. We argue that emotion signals the need for and provides the energy that fuels sensemaking, and that different kinds of emotions are more and less likely to play these roles. Second, we explore the role of emotion in shaping sensemaking processes, focusing on how emotions make sensemaking a more solitary or more interpersonal process, and a more generative or more integrative process. Third, we argue that sensemakers’ felt emotion plays an important role in concluding sensemaking, particularly through its effect on the plausibility of sensemaking accounts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.764
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.019
GPT teacher head0.274
Teacher spread0.254 · 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