Dynamic Regulatory Constitutionalism: Taking Legislation Seriously in the Enforcement of Economic and Social Rights
Bibliographic record
Abstract
Since the global acknowledgement that economic and social rights can be entrenched alongside civil and political rights in domestic constitutions, four dominant models for the judicial enforcement of these rights have emerged: structural injunctions, the minimum core approach, the administrative law approach, and the ‘dialogic’ or ‘conversational’ models. This paper argues that each of these approaches fails to pay sufficient attention to the role of legislation in communicating a legal community’s fundamental normative commitments to the officials responsible for implementing economic and social rights. In situations where ‘social legislation’ has been enacted to structure official efforts to realize economic and social rights, this inattention to normativity caries a risk that officials will comply formally with statutory rules without a consideration of whether their conduct promotes the normative objectives of the legislation. In turn, courts will be required to intervene more frequently to uphold rights where official conduct is incongruent with the normative commitments of social legislation. This paper proposes that courts should uphold ‘normative congruence’ by ensuring that official conduct under social legislation is congruent not only with the formal terms of that legislation but also with the normative commitments it expresses. Courts should engage with officials to ascertain whether official conduct is based on an understanding of how normative commitments inflect the statutory rules that govern their conduct, and lead officials towards an understanding of this connection where it is lacking. Judicial engagement with officials in upholding normative congruence is a form of ‘dynamic regulatory constitutionalism’ that orients officials to the normative content of social legislation. The judicial enforcement of economic and social rights, whichever of the existing models a court employs, should proceed only on the foundation of this normatively rich dynamic regulatory constitutionalism.
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 | 0.032 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.071 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".