Recognizing the Best: The Productive and Counterproductive Effects of Relative Performance Recognition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract I use a laboratory experiment to examine the productive and counterproductive effects of providing employees nonpecuniary recognition based on measures of relative performance. I find that, on average, recognition programs increase both productive efforts (those intended to increase one's own performance) and counterproductive efforts (those intended to decrease peer performance) in a setting where it is salient to employees that they can exert both productive and counterproductive efforts. Interestingly, I also find that these effects are moderated by the Dark Triad of personalities, a group of three personality traits. My study reveals that recognition programs mainly lead individuals who score lower on the Dark Triad to increase counterproductive efforts and those who score higher on the Dark Triad to increase productive efforts. These results contribute to the literature on relative performance information by demonstrating that recognition programs can have both productive and counterproductive effects. However, whether these programs produce mainly a productive or counterproductive effect depends on important personality characteristics of the employees.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it