An empirical analysis of surface acting in intra‐organizational relationships
Bibliographic record
Abstract
Summary Prior research analyzing surface acting—employees' regulation of emotional expressions—has mostly focused on the interactions between front‐line employees and their customers in service industries and paid very little attention to intra‐organizational relationships. With an aim to shed light on this important yet relatively unexplored area, I developed a theoretical model analyzing the antecedents and outcomes of surface acting within organizations, by drawing on the sociometer theory and self‐presentation theory frameworks. To test the model, I conducted a cross‐level field study in a sample of 65 work groups and 478 employees in two organizations, located in a large city in Northern California. I have collected the data from two sources, including employees and their supervisors who rated their performance. Results indicated that employees were more likely to engage in surface acting when their affective traits and personal goals were less congruent with work environment. Surface acting was also positively related to perceived organizational politics and self‐monitoring. As for outcomes, surface acting was positively related to emotional exhaustion and negatively to performance. I discuss limitations, implications, and future research direction. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".