Individual Decision-Making Underlying the Tragedy of the Commons
Bibliographic record
Abstract
ABSTRACT Group decision-making is common in everyday life, whether a family is sharing a meal or a corporation is dividing profits. Research in economics on group decision-making has coalesced into a theory known as the tragedy of the commons, which states that resources are inevitably overused when shared by a group. However, even while multiple approaches to mitigating overuse of common resources have been put forward, notable counterexamples to the tragedy of the commons exist such that groups are ultimately able to avoid resource overuse. Development of a computerized paradigm amenable to behavioral modeling and simulation analyses could allow for exploration of whether resources will be overused in a given group of individuals and allow for the rapid testing of behavioral interventions designed to reduce instances of resource overuse. Using a newly developed group decision-making task, we studied how participants made decisions to utilize shared resources for the potential to receive a larger amount of money or conserve resources for a smaller amount of money. Using behavioral modeling, we found that valuation of resource overuse is most impacted only when an exceptionally small amount of resources are remaining. Using computational analyses, we were able to differentiate individual participants by both group earnings and self-reported social attitudes in ways that correlated with their willingness to utilize resources. These results signify the importance of individual differences in group composition regarding the tragedy of the commons, emphasizing the impact of the attitudes and behaviors of individual group members in predicting shared resource use.
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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 | 0.002 | 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 | 0.000 |
| Open science | 0.002 | 0.003 |
| 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 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".