The Influence of a Manager's Own Performance Appraisal on the Evaluation of Others
Bibliographic record
Abstract
This study examined the possibility that the performance appraisal process is affected by a pervasive and inherent effect that has heretofore been unidentified. This effect derives from the results of the performance appraisal most recently performed on the manager who subsequently conducts appraisals of others. The nature of this effect was examined in four studies. In a case study, the ratings received by two area coordinators in a university academic department affected their subsequent ratings of faculty. In a simulation, 30 managers received hypothetical feedback regarding their own job performance. The managers subsequently evaluated an employee on videotape. Managers who received positive feedback about their performance subsequently rated the employee significantly higher than managers who received negative feedback regarding their own performance. This occurred despite the fact that the managers knew the evaluation of them was bogus. The results of two follow‐up field studies involving 74 manager–employee dyads in a manufacturing company in Canada and 39 manager–subordinate dyads in a retail organization in Turkey are consistent with the view that one's own performance appraisal is related to the subsequent appraisal of one's subordinates. Both anchoring with insufficient adjustment and a mood induction may explain this effect, but the results are more consistent with the former explanation than the latter.
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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 | 0.001 | 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) | 0.000 | 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".