Can group rewards promote helping in asymmetrically imbalanced task relationships?
Bibliographic record
Abstract
This paper investigated whether group-level rewards can counteract the negative effects of asymmetric task dependence. Previous research has found that asymmetry (an imbalance in task-related resources, such as work inputs, knowledge, or skills) is correlated with lower levels of helping behavior. In this study, 182 students participated in a work simulation that manipulated symmetry and reward interdependence, and measured helpful behaviors provided to the dependent. The results demonstrate that asymmetry indeed leads to selfish behavior. However, group-level rewards are an effective way to motivate resource controllers to give help to their dependents. Interestingly, group rewards motivate over and above the benefit received from the reward itself—although resource controllers could maximize their own benefit with 2 helping behaviors per round, they gave on average 3.7 to 6.4 helping behaviors per round (95% confidence interval based on 10,000 bootstrap samples). The results demonstrate that in an asymmetrically dependent relationship, group-level rewards can motivate helping behavior over and above rational self-interest.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".