Bibliographic record
Abstract
In the last two decades, the economy has undergone fundamental transformation with the twin structural changes of a great increase in the size of global markets and the internet-driven development of a platform for global exchange and work processes. These changes have transformed the economic demand for law: the demand for legal inputs that will support the creation of value in economic relationships. Not merely the quantity but the type of legal inputs required by the new economy is significantly different from those required by the old economy. The economic demand for law in the new economy requires support for the much higher rates at which economic relationships now cross both firm and jurisdictional boundaries, the more rapid depreciation of legal solutions, the increased differentiation of legal problems, the reduced tolerance for legal transaction costs created by high velocity and global competition, and a greater need for integration of business and legal expertise in order to engage in the relatively constant innovative problem-solving that the new economy requires. In this paper I argue that our legal infrastructure - the socially available set of legal materials that economic actors can use to help govern relationships - has not kept up with this transformation in the economic demand for law. Empirical evidence for this claim includes the increasing levels of dissatisfaction in even the most elite corporate legal markets, the unprecedented impact of the Great Recession of 2009 on large law firms, and surveys and interviews conducted with corporate counsel. The primary basis for the claim of a mismatch, however, is theoretical: the attributes of our existing legal infrastructure - a heavy reliance on densely-worded and complex statutes, regulations and contracts; human-capital-intensive craft production methods; undiversified legal business models; almost exclusive reliance on mandatory legal rules imposed by public actors - are poorly suited to the nature of economic activity in the new economy. The reason our legal infrastructure has not adapted, I argue, is attributable to an even deeper level of legal infrastructure: the severe limitations on who may produce legal rules and other legal inputs (such as advice, document templates, norms and practices) imposed by our continued reliance on publicly produced rules and the excessively closed nature of our lawyer- and judge-controlled legal markets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".