Good Fences Make Good Neighbors: Endogenous Property Rights in a Game of Conflict
Bibliographic record
Abstract
This paper derives the conditions under which property rights can arise in an anarchy equilibrium. The creation of property rights requires that players devote part of their endowment to the public good. In the Nash equilibrium, no player contributes to the provision of property rights protection. Therefore, players are left with two alternatives. A king who provides property rights protection paid for by a tax on endowments completely eliminates conflict. However, a king who can eliminate conflict can also take the surplus for himself. As a despotic king inefficiently taxes endowments, players have an incentive to find a solution that keeps power in their own hands. Thus in a social contract, players first credibly commit part of their endowments to providing property rights and then allocate the balance of their endowments between production and conflict. A social contract can also drive conflict to zero. However, as the number of players rises, the private provision of property rights through a social contract results in positive levels of conflict and lower levels of aggregate welfare than under a benevolent king.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".