Endangered Resources: The Role of Organizational Justice and Interpersonal Trust as Signals for Workplace Corruption
Bibliographic record
Abstract
This study examines workplace corruption from the perspective of individual psychological processes. Existing literature has shown how corrupt behaviours can emerge from various kinds of motivations, including manipulation, retaliation, and conformity. This research suggests yet another path, where corruption stems from a motivation to preserve resources that individuals perceive to be threatened by their professional environment. As such, the study is grounded in conservation of resources (COR) theory (Hobfoll, 1989, 2001). We put forward an original model that introduces the notion of resource signals. An enrichment of original COR theory, resource signals correspond to individuals’ perceptions that the work environment is supportive, or, otherwise, of their need for resource development and preservation. Specifically, the study tests a moderated mediation model where a sense of mastery, a personal resource, moderates the impact of resource signals, including distributive justice, procedural justice, and interpersonal trust, on occupational corruption. Results are drawn from a sample of French public sector employees (n = 575). They validate the hypothesized mediating role of trust between both facets of organizational justice and measures of corruption, including bribery and property deviance. An indirect negative effect, however, is strongest between procedural justice and workplace corruption. As hypothesized, a sense of mastery significantly moderates the link between trust and both corruption types. This research contributes to both theory and practice. By integrating resource signals within a COR framework, it shows that corrupt behaviours are to be gauged against interacting motivations for preserving psychological resources. Consequently, this study also suggests that organizations should go beyond ethics and procedures, and to consider workplace corruption as a potential symptom of organizational signals perceived as threats to individuals’ valued resources.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".