Bibliographic record
Abstract
This article provides an explanatory framework of the spontaneous lawmaking (“SL”) process in the area of private law. To illuminate the process of the spontaneous emergence of private law, this paper focuses on three issues: (1) the conditions under which SL is likely to generate efficient norms, (2) the mechanisms that explain the emergence of norms in the absence of centralized enforcing institutions, and (3) the comparative advantages and disadvantages in terms of the efficiency of SL compared to public centralized lawmaking processes. This discussion is organized as follows. Section I defines the scope of the analysis. Section II introduces the relevant analytical tools offered by game theory and transaction-cost economics. Section III identifies the conditions for the spontaneous emergence of efficient norms. Section IV identifies three alternative mechanisms that explain the spontaneous emergence of norms. Section V examines the limitations of SL processes. Finally, Section VI provides examples of SL in the area of private law to demonstrate concretely the analytical potential of the proposed framework.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".