Thank You! Exploring the Impact of Gratitude in Organizational Relationships
Bibliographic record
Abstract
Recently, the broader psychology literature has demonstrated the importance of gratitude in human relationships. Despite this evidence that gratitude is central to effective relationships, research on gratitude in organizational relationships has received little attention. This symposium seeks to address this gap by examining the role of gratitude in organizations. The symposium includes four empirical papers--two field experiments and two field studies--that explore the influence of gratitude on beneficiaries, their coworkers, and their organizations. Specifically, the studies in the symposium examine the role of gratitude in informing the meaning of one’s work and motivating performance, the importance of appreciation in supervisor/subordinate relationships, the explanatory power of gratitude in understanding employees’ reactions to receiving OCB at work, and the downside of grateful feelings for professional colleagues. These papers extend our understanding of organizational gratitude by considering novel contexts and novel outcomes. We hope the symposium will highlight the importance of this topic and stimulate future research. Appreciation in Supervisor-Subordinate Relationships Presenter: Sharon Sheridan; U. of Central Florida Presenter: Maureen L. Ambrose; U. of Central Florida Presenter: Craig D. Crossley; U. of Central Florida Finding Meaning in Seemingly Meaningless Work:How the Words of Beneficiaries Influence Performance Presenter: Paul Green; Harvard Business School Presenter: Francesca Gino; Harvard U. Presenter: Bradley R Staats; U. of North Carolina, Chapel Hill Breaking Rules for Relationship-Promotion: The Interactive Effects of Gratitude and CSE Presenter: Jennifer A. Harrison; NEOMA Business School Presenter: Marie-Helene Budworth; York U. Presenter: Amanda Shantz; IESEG School of Management Testing if State Gratitude Mediates the Relation between Received and Enacted OCB Presenter: Patricia L. Baratta; U. of Guelph Presenter: Denise Luta; U. of Guelph Presenter: Jeffrey R. Spence; U. of Guelph
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".