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Record W4403337198 · doi:10.1177/03128962241286180

The emergence of team compassion: Theoretical implications and practical interventions

2024· article· en· W4403337198 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.

Bibliographic record

VenueAustralian Journal of Management · 2024
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychological interventionCompassionPsychologyBusinessEconomicsPolitical science

Abstract

fetched live from OpenAlex

With the recent experiences involving COVID-19, there is a growing need for organisations to better understand compassion in addressing employees’ suffering and boosting their well-being. Particularly, as teamwork is becoming ubiquitous, organisational scholars have identified positive benefits of compassion at the team level such as improving communication, decreasing interpersonal conflicts and boosting team effectiveness. Using a multilevel theoretical framework in reviewing compassion research, this article advances our understanding of team-level compassion by elucidating the processes through which individual-level compassion gives rise to team-level compassion. First, we delineate composition and compilation models of the emergence of team compassion and review empirical studies with respect to the two models. Second, we explain three social mechanisms in teams – social learning, emotional contagion and reciprocity – that shape the emergence of team compassion. Finally, we discuss interventions that can facilitate the emergence of team compassion and offer practical guidance for managers seeking to foster team compassion. JEL Classification: D23, I31

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.110
GPT teacher head0.465
Teacher spread0.355 · 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