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Interpersonal Interactions and Employee Well-Being: Exploring Coworker, Leader, and Follower Roles

2025· article· en· W4416002110 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

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldPsychology
TopicTransactional Analysis in Psychotherapy
Canadian institutionsSimon Fraser UniversityYork University
Fundersnot available
KeywordsGratitudeInterpersonal communicationInterpersonal relationshipFeelingPerspective (graphical)SAINTScale (ratio)

Abstract

fetched live from OpenAlex

Interpersonal interactions are ubiquitous in daily work life, shaping relevant employee outcomes. This symposium focuses on the unique role of interpersonal processes in determining employees’ optimal functioning at work as captured by well-being while also accounting for individual performance. The presentations differentiate the diverse roles employees can occupy in interpersonal interactions, such as being a leader, a follower, and a coworker. Additionally, the presentations capture the full spectrum of interaction valence, ranging from clearly positive or negative interactions to ambiguous interpersonal processes. Thereby, the studies included in this symposium pursue novel theoretical and methodological approaches to move interpersonal research forward. The Impact of Gratitude Variability on Employee Well-Being Author: Meghan Kane; University of Central Florida Author: Lauren Rachel Locklear; Texas Tech University Author: Mark G. Ehrhart; University of Central Florida Putting Leaders Down: The Consequences of Feeling Underappreciated by Followers Author: Daniel Kim; Author: Klodiana Lanaj; University of Florida Author: Remy E. Jennings; Florida State University Author: Yejoo Lee; University of Florida Author: Alex Settles; University of Florida Inconsistent Leadership: Scale Development and Validation Author: Duygu Biricik Gulseren; York University Author: Zhanna Lyubykh; Simon Fraser University Author: Langxi Wang; Saint Mary's University Author: E Kevin Kelloway; Saint Mary's University The Double-Edged Sword of Leader Performance Expectations: A Diary Study Author: Julia Iser-Potempa; University of Mannheim Author: Jette Völker; University of Mannheim Relational Boundary Management at Work: A Boundary-Theory Perspective on Coworker Interactions Author: Jette Völker; University of Mannheim Author: Julia Iser-Potempa; University of Mannheim Author: Anna Neumer; University of Mannheim

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 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 score0.556
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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