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Record W4383876884 · doi:10.1111/joms.12976

Beyond the Feeling Individual: Insights from Sociology on Emotions and Embeddedness

2023· article· en· W4383876884 on OpenAlexaff
Rongrong Zhang, Maxim Voronov, Madeline Toubiana, Russ Vince, Bryant A. Hudson

Bibliographic record

VenueJournal of Management Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of OttawaYork University
Fundersnot available
KeywordsEmbeddednessSociologyFeelingPhenomenonSocial capitalFocus (optics)Social psychologyEpistemologyPsychologySocial science

Abstract

fetched live from OpenAlex

Abstract Organizational scholars have treated emotions mostly as an individual‐level phenomenon, with limited theorisation of emotions as an important component in social embeddedness. In this review essay, we argue for the need for a toolkit to study emotions as an inherently social phenomenon. To do so, we apply insights from sociology that have been under‐utilized in management and organization research. We focus on three sociological concepts: collective emotions and social bonds, emotional energy and moral batteries, and emotional capital. We then develop an integrative model of emotional embeddedness to emphasize that emotions are socially constructed and socially authorized. We end the paper by setting out a research agenda for more research in management and organization that is informed by these three concepts.

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)0.000
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 score0.456
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.041
GPT teacher head0.273
Teacher spread0.232 · 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 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

Citations39
Published2023
Admission routes1
Has abstractyes

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