Neither ‘Public’ nor ‘Private’, ‘National’ nor ‘International’: Transnational Corporate Governance from a Legal Pluralist Perspective
Bibliographic record
Abstract
This paper contends that the challenging nature of the regulation of global corporate conduct requires an adequately differentiated approach towards the identification and analysis of the norms in question. In part I, I review the context of ‘state intervention’ and ‘market self‐regulation’, in which the current discussion of regulatory responses to the economic/financial crisis and the role of self‐regulation occurs, before laying out the concept of ‘transnational legal pluralism’ in part II. In part III, I argue that an exemplary area such as corporate governance can best be understood as an instance of transnational legal pluralism, a field that becomes visible through a particular methodological lens. In part IV, I conclude by suggesting how the lessons of such a case study can contribute to an ongoing theoretical investigation into the nature of global regulatory governance, using the concept of ‘rough consensus and running code’.
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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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| 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".