Helping as an opportunity and risk: an alternative side to gratitude in co-worker dyads
Bibliographic record
Abstract
Purpose As workplaces and relationships evolve with increasing complexity, co-worker dynamics have become a key concern for HR managers and scholars. An important yet overlooked aspect of co-worker dynamics is gratitude. This paper adopts a relationship-specific conceptualization of gratitude and explores its influence on prosocial behaviors within co-worker dyads. The proposed model also suggests structural-relational factors under which these relationships are affected. Design/methodology/approach The conceptual paper draws insights from personal relationships to consider an alternative side of gratitude’s prosocial action tendencies, thereby highlighting two: risk-oriented and opportunity-oriented. These assumptions are then situated within the affect theory of social exchange to predict gratitude’s influence on prosocial behaviors within co-worker dyads. Findings The proposed model illuminates the importance of studying relationship-specific gratitude within co-worker relations by illustrating its effects on two types of prosocial action tendencies – opportunity-oriented and risk-oriented and varying prosocial behaviors (from convergent to divergent). Structural-relational factors, such as positional and physical distance between co-workers, are considered to affect these relationships. Originality/value While the study of gratitude in the workplace is emerging, little research has examined its influence on the nature of prosocial behaviors within co-worker relations. This paper advances the notion that gratitude serves an adaptive function in co-worker dyads, thereby highlighting the risk-oriented and opportunity-oriented continuum, and its implications for the type and scope of prosocial behaviors exchanged.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".