The Distribution of Power Over Social Distancing Regulation in the UK: Constitutional Design Principles from Economic Theory
Bibliographic record
Abstract
Which groups of elected officials should be in charge of decisions about the imposition of lockdowns and other social distancing rules? People throughout the UK have debated this issue since the start of the pandemic. When central government, local governments, and devolved administrations all enjoy democratic legitimacy, disputes over who should have the power to impose social distancing rules are almost inevitable. The nature of the British constitution also means that the recent debates about parliamentary insight and social distancing rules were predictable. This paper sheds lights on these debates over who should have the power to impose social distancing rules by drawing on economic theory, particularly the work of Nobel Laureates Hayek (1945) and Ostrom (1990). We review UK policy since March 2020 using this lens and then present policymakers with actionable recommendations. We argue that local rather than national governments should be given authority over whether or not to impose lockdowns and similar measures. We argue that in areas in which local government powers are not unified into a single unit and instead dispersed to different levels (e.g. county and borough councils), power over social distancing rules should be vested in the most junior unit of government. We use economic theory to argue that the legislative branches within each level of government should exercise close and continuous parliamentary oversight of all social distancing rules. In light of this pandemic, the UK might also consider investing resources in acquiring a written constitution that would clearly specify who has power over public health measures such as social distancing rules.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".