The relationship between job standardization and abusive supervision
Bibliographic record
Abstract
Abstract Job standardization is widely used to ensure uniform, efficient, and effective production and resultant organizational performance. However, phenomena suggests that employees with high job standardization seem to have a negative relationship with their supervisors. Using job demands–resources theory as an underlying explanation, this study proposes that job standardization enhances a negative supervisor–subordinate relationship characterized by abusive supervision. Three‐wave panel and two‐source survey data were collected from 255 employees and their supervisors. Empirical results indicated job standardization enhanced abusive supervision partially through the decreased appraisal respect of subordinates for supervisors and that of supervisors for subordinates. The results indicate a dilemma in employing the job design of standardization: on the one hand, it facilitates managerial effectiveness; on the other hand, it can decrease that effectiveness by deteriorating the supervisor–subordinate relationship. This study extends and shifts the understanding of the consequences of job standardization from the employee perspective to the managerial perspective.
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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 | 0.024 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".