Contributions to a Post-Sovereigntist Understanding of Law: Foucault, Law as Governance, and Legal Pluralism
Bibliographic record
Abstract
This article proposes an understanding of law that goes beyond the popular association of law with sovereignty, constitutionalism and representative political institutions. By drawing on insights provided by the law as governance and `non-essentialist version of legal pluralism' approaches, the focus is on retrieving the specificity of plural legal and normative ordering strategies. The law as governance approach proposes a modest role for law where law is conceived as connectively situated among a multiplicity of other constitutive modes of regulation. The `non-essentialist version of legal pluralism' is a conventionalist rearticulation of the hitherto unproblematized tradition of legal pluralism. Comparing the law as governance and `non-essentialist version of legal pluralism' approaches contributes to a post-sovereigntist understanding of law. A post-sovereigntist understanding of law focuses on the state as a site for the unification of regulatory projects, but, inspired by Michel Foucault's later works, finds it important to place analyses of law within the context of a decentered economy of productive power and extensive government. This post-sovereigntist understanding not only provides a clearer depiction of the way legal and normative ordering and their interrelations work in the everyday, but raises questions regarding the future of legal pluralism in socio-legal theory.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.078 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".