Introduction - Reading Modern Law: Critical Methodologies and Sovereign Formations
Bibliographic record
Abstract
Reading Modern Law identifies and elaborates upon key critical methodologies for reading and writing about law in modernity. The force of law rests on determinate and localizable authorizations, as well as an expansive capacity to encompass what has not been pre-figured by an order of rules. The key question this dynamic of law raises is how legal forms might be deployed to confront and disrupt injustice. The urgency of this question must not eclipse the care its complexity demands. This book offers a critical methodology for addressing the many challenges thrown up by that question, whilst testifying to its complexity. The essays in this volume - engagements direct or oblique, with the work of Peter Fitzpatrick - chart a mode of resisting the proliferation of social scientific methods, as much as geo-political empire. The authors elaborate a critical and interdisciplinary treatment of law and modernity, and outline the pivotal role of sovereignty in contemporary formations of power, both national and international. From various overlapping vantage points, therefore, Reading Modern Law interrogates law's relationship to power, as well as its relationship to the critical work of reading and writing about law in modernity.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".