Subjectivity in Professionals' Incentive Systems: Differences between Promotion‐ and Performance‐Based Assessments
Bibliographic record
Abstract
Abstract We examine how managers assess performance and promotion prospects—that is, the ex ante likelihood of promotion—and the conditions under which these assessments diverge. We argue that managers apply different cognitive schemas when they make different assessments. To the extent that a signal provides different information about future versus current contributions, assessed performance and promotion prospects are likely to diverge. In two experiments, we manipulate professionals' promotion eligibility and level of consultative decision making. We find that experienced managers assess performance and promotion prospects differently, but only when professionals are promotion eligible. Specifically, more (as opposed to less) consultative decision making decreases promotion prospects while not affecting assessed performance (Experiment 1) or even improving it (Experiment 2). By contrast, more consultative decision making improves both assessments when professionals are not eligible for promotion. We shed light on the relations between subjective assessments, including that promotion is not necessarily the consequence of superior assessed 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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".