Against Constitutional Excess: Tocquevillian Reflections on International Investment Law
Bibliographic record
Abstract
Contributing to democratic malaise in operative democracies are transnational constitution-like commitments, such as those found in international investment law. Among its constraints, citizens are legally discouraged from initiating policy innovations that will upset investment expectations. Yet, one of the great virtues of democratic society, according to Alexis de Tocqueville, is the capacity of people to change their minds: an ability to repair mistakes. Though the threat of continual legislative innovation resulted in costly instability, it served as a catalyst for an energetic public and private life. So as to tame the threat of intemperate change, Tocqueville looked to the guiding hand of lawyers and judges—the functional equivalent of an aristocracy—to moderate majoritarian excess. International investment lawyers have lost sight of the equilibrium that Tocqueville envisaged, privileging legal disciplines over the ability of democratic polities to experiment and innovate. For Tocqueville, democratic life would be intolerable and citizens reduced to a “herd of timid and industrious animals” if too many constraints were placed upon legislative energy. This Essay brings Tocqueville’s lessons to bear on the field of international investment law. It pleads for a reduction in the influence of lawyers and their legal strictures, beyond those constraints contained in national constitutional systems, on democratic practice.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".