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Record W4384827283 · doi:10.3389/fcomm.2023.1144045

Communicating compassion in organizations: a conceptual review

2023· review· en· W4384827283 on OpenAlexafffund
Kirstie McAllum, Stéphanie Fox, Jessica L. Ford, Arden C. Roeder

Bibliographic record

VenueFrontiers in Communication · 2023
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCompassionPsychologySocial psychologyCLARITYSubject (documents)EpistemologyPolitical scienceComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This article explores the theoretical terrain surrounding compassion in organizational settings to clarify how conceptually (dis)similar concepts like social support, team care, and organizational compassion manifest different agentic perspectives on compassion. Toward this end, we articulate a working definition of compassion and suggest that a communicative frame focused on intersubjective sense-making and interpretation can deepen our understanding of who is responsible for care and compassion within organizations. Existing research on this subject considers who or what provides compassion—individuals, teams, policies—and how compassion can assuage suffering and promote individual and organizational flourishing. Extending this work, we document core dimensions of each form of compassion for greater conceptual clarity and precision, proposing a metaphor for each. Finally, we reflect on the implications of each type of compassion for resilience and the ways current notions of compassion typify the rationality/emotionality duality and gendered nature of emotion work in organizations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.008
Science and technology studies0.0010.004
Scholarly communication0.0040.005
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.070
GPT teacher head0.335
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations17
Published2023
Admission routes2
Has abstractyes

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