Too drained to help: A resource depletion perspective on daily interpersonal citizenship behaviors.
Bibliographic record
Abstract
This article explores the role of within-person fluctuations in employees' daily surface acting and subsequent personal energy resources in the performance of organizational citizenship behaviors directed toward other individuals in the workplace (OCBI). Drawing on ego depletion theory (Muraven & Baumeister, 2000), we develop a resource-based model in which surface acting is negatively associated with daily OCBIs through the depletion of resources manifested in end-of-day exhaustion. Further integrating ego depletion theory, we consider the role of employees' baseline personal resource pool, as indicated by chronic exhaustion, as a critical between-person moderator of these within-person relationships. Using an experience-sampling methodology to test this model, we found that surface acting was indirectly related to coworker ratings of OCBI through the experience of exhaustion. We further found that chronic levels of exhaustion exacerbated the influence of surface acting on employees' end-of-day exhaustion. These findings demonstrate the importance of employees' regulatory resource pool for combating depletion and maintaining important work behaviors. Implications for theory and practice are discussed.
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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 | 0.001 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".