What about ‘MEE’: A Measure of Employee Entitlement and the impact on reciprocity in the workplace
Bibliographic record
Abstract
Abstract A basic underlying assumption of the psychological contract is that both parties come to a mutual agreement about the expectations and obligations of a contract of employment. Recent research provides evidence of the potential for employees to develop unrealistic expectations from this contract and this has been described as a sense of entitlement. In this article, we outline two studies. In the first study, we test the internal structure and reliability of a scale we developed and named the Measure of Employee Entitlement. In the second study, we test the predictive validity of the Measure of Employee Entitlement against a measure of reciprocity. The development and validation of the Measure of Employee Entitlement extends our knowledge of sense of entitlement in the workplace and situates entitlement as a factor that may impact on the development of psychological contracts. This research provides a platform from which researchers and practitioners can continue to coherently and consistently investigate the phenomenon of employee entitlement.
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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 | 0.006 | 0.035 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".