The two faces of envy: perceived opportunity to perform as a moderator of envy manifestation
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate, with a Pakistani sample, the destructive and constructive behavioral intentions associated with benign and malicious envy in the context of perceived opportunity to perform. Design/methodology/approach The authors conducted two cross-sectional studies to test the hypotheses. In Study 1, data were obtained from students (n=90), whereas in Study 2, the authors used an executive sample (n=83). Findings The primary motivation of benign envy was to bring oneself up by improving performance on the comparison dimension, whereas the primary motive of malicious envy was to pull the envied other down. The relationship between malicious envy and behavioral “pulling down” intentions of derogating envied other was conditional on perceived opportunity on the comparison dimension. Consistent with a motive to improve self-evaluation, this study also found that perceived opportunity to perform interacted with benign envy to promote performance intentions on an alternative dimension. Furthermore, malicious envy was also associated with self-improving performance intentions on the comparison dimension, conditional upon perceived opportunity to perform. Practical implications Envy, depending on its nature, can become a positive or negative force in organizational life. The pattern of effects for opportunity structure differs from previous findings on control. The negative and positive effects of malicious envy may be managed by attention to opportunity structures. Originality/value This study supports the proposition that benign envy and malicious envy are linguistically and conceptually distinct phenomena, and it is the first to do so in a sample from Pakistan, a non-western and relatively more collectivistic culture. The authors also showed that negative and hostile envy-based behaviors are conditional upon the perceived characteristics of the context.
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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 | 0.007 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".