When Peer Recognition Backfires: The Impact of Peer Information on Subsequent Helping Behavior*
Bibliographic record
Abstract
ABSTRACT Peer recognition systems (PRS) have gained popularity in recent years as a means for organizations to promote employee helping behavior. However, there are theoretical reasons to believe that peer information that is publicly disclosed in PRS may reduce subsequent helping behavior, and I use an experiment to test my theory. Specifically, I examine a three‐employee setting where an employee (the worker) receives no recognition for helping a coworker (the recognizer) but another coworker (the helper) does. I predict and find that the worker's willingness to subsequently help the recognizer/helper is lower when the worker perceives that the worker's initial help exceeds (vs. subceeds) the helper's. I also find that the worker's perception of fairness mediates the process, and the worker's willingness to help the recognizer has a spillover effect on the worker's willingness to help the helper. My study provides the first empirical evidence of the negative impact that PRS have on helping behavior.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".