Virtual Work Environments as a Situational Antecedent of Employee Entitlement
Bibliographic record
Abstract
There exists a large body of literature exploring employee entitlement as a factor of narcissism. The present research explores employee entitlement’s latent potential under a trait-activation framework. Providing information to guide the future conceptualizations of employee entitlement is one goal of the present research. A second goal is to assess whether virtual work environments, compared to in-person work environments, activate the expression of latent entitlement. The last goal is to investigate if the perception of a comparative and objective feedback system influences employee entitlement in either work environment. Amazon Mechanical Turk workers identified as holding one full-time employment position, 18 years or older, and a resident in Canada or the USA completed the study’s online survey (n = 93). Findings do not indicate that employee entitlement is activated differently across virtual and in-person work environments. Findings indicate that when employees perceive the performance appraisal system as objective and comparative, they report higher levels of entitlement as measured with perceptions of reward deservingness. The perception of an objective and comparative performance appraisal system as a positive predictor of reward deservingness indicates that entitlement may exist as the disparity between work performance and reward beliefs. The results indicate that after receiving objective and comparative feedback employees may improve work performance to justify initial high reward deservingness beliefs. Future research should seek to explore whether employees differently interpret behaviors as more or less entitled based on work performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".