When Competence Is Irrelevant: The Role of Interpersonal Affect in Task-Related Ties
Bibliographic record
Abstract
This paper examines the role of a person's generalized positive or negative feelings toward someone (interpersonal affect) in task-related networks in organizations. We theorize that negative interpersonal affect renders task competence virtually irrelevant in a person's choice of a partner for task interactions but that positive interpersonal affect increases a person's reliance on competence as a criterion for choosing task partners, facilitating access to organizational resources relevant to the task. Using social psychological models of interpersonal perception and hierarchical Bayesian models, we find support for this theory in social network data from employees in three organizations: an entrepreneurial computer technology company, staff personnel at an academic institution, and employees in a large information technology corporation. The results suggest that competence may be irrelevant not just when outright dislike colors a relationship. Across organizational contexts and types of task-related interaction, people appear to need active liking to seek out the task resources of potential work partners and fully tap into the knowledge that resides in organizations. We discuss contributions of our study to research on the interplay of psychological and structural dimensions of organizational life.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".