Shut Up and Fish: The Role of Communication when Output-Sharing is used to Manage a Common Pool Resource
Bibliographic record
Abstract
Schott et al. (2007) have shown that the “tragedy of the commons” can be overcome when individuals share their output equally in groups of optimal size and there is no communication. The assignment of individuals to groups as either strangers or partners does not significantly affect this outcome. In this paper we investigate whether communication changes these results. Communication reduces shirking, increases aggregate effort and reduces aggregate rents, but only when communication groups and output-sharing groups are linked. The effect is stronger for fixed groups (the partners treatment) than for randomly reassigned groups (the strangers treatment). Performance is not distinguishable from the no- communication treatments when communication is permitted but subjects share output within groups different from the groups within which they communicate. Communication also tends to enhance the negative effect of the partnered group assignment on the equality of individual payoffs. We use detailed content analysis to evaluate the impact of various categories of communication messages on behaviour across treatments.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| 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".