Bibliographic record
Abstract
States of emergency may play a unique role in constitutional practice and theory. A comparison of constitutional orders reveals that they have to choose between seeking to entrench in a written constitution, if they have one, rules about how the state may respond to an emergency, and leaving such responses to be decided as and when an emergency occurs. This article sets out some examples of constitutional design and looks at some examples of constitutional practice show the basis for the Schmittean view of states of emergency and their implications for constitutionalism. The ramifications of this issue go far beyond states of emergency, a phenomenon of which lawyers and political scientists in the United States are well aware as they seek to deal with the way in which the office of the president and the executive in general seem increasingly free of constitutional and legal constraints. But the examples hardly tell unambiguously in favour of Schmitt. Indeed, they might serve to show that the constitutional choice is not between various institutions — the executive, the legislature and the judiciary — but between a vacuous or merely procedural account of legality and one that links procedure to substance. Moreover, the latter requires that all three powers work together in ensuring that responses to emergencies accord with constitutional principles.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.008 |
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".