(Mis)Aligned? How Managers’ and Employees’ Red Tape Perceptual (Dis)Agreement Shapes Mission Valence
Bibliographic record
Abstract
Red tape is an important feature of the daily reality of most public managers and employees. Research has shown that perceived red tape has however mainly focused on the perceptions of employees and managers in isolation. In this study, we argue that employees' reactions to red tape do not form in silos and are intricately linked to social interactions at work. Building on this assumption, we explore the supervisor-employee (dis)agreement about red tape and examine its effects on employees’ perception of mission valence and subsequent work attitudes. Using polynomial regressions among a sample of 291 supervisor-employee dyads working in three public administration departments, we find that employee mission valence is lower when a) when both parties agree that red tape is high; b) the employee perceives less red tape than their leader. Our results also show that the agreement configurations are related to job engagement and affective commitment through perceptions of mission valence (mediator).
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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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".