Choice-of-Law Rules for Secured Transactions: An Interest-Based and Modern Principles-Based Framework for Assessment
Bibliographic record
Abstract
This essay examines the law applicable to secured transactions. It addresses in particular the codification of the choice-of-law rules for secured transactions (STCOL rules). These rules address the laws applicable to the creation, perfection, priority, and enforcement of security interests (security rights)—a form of legislative or statutory dépeçage. It draws on the 2016 UNCITRAL Model Law on Secured Transactions (Model Law) as well as relevant North American law (Uniform Commercial Code Article 9 and the Canadian provincial Personal Property Security Acts). The STCOL rules lie at the heart of the emerged and emerging modern principles of secured transactions law (Modern Principles) for personal property (movable assets). These Modern Principles are reflected by the Model Law and North American law as well as by various other model laws, other secured transactions ‘reforms’ over recent years, and laws that are currently being considered by various States. While disagreements exist, debates continue, and strict harmonization is unlikely, there is little doubt that there has emerged a global consensus as to a set of general principles to which secured transactions law should adhere.The STCOL rules and their relationship to substantive legal doctrine remain somewhat underdeveloped and undertheorized. This essay seeks to remedy this situation. It situates the STCOL rules as fundamental components of secured transactions law and central to understanding the normative principles and factual assumptions underpinning that important body of law. Its principal contribution is to offer a framework for assessing the existing STCOL rules and for the codification of future rules. The framework is based on the interests of stakeholders that participate in or are affected by secured transactions and the Modern Principles. These stakeholders include third parties in general, assignors and assignees of security rights, third-party obligors on assigned assets (such as debtors on an assignor’s receivables), and the States that enact and whose interests are affected by STCOL rules. This framework also illuminates the factual bases for its application. But it can evaluated only through its application and analysis, which necessarily produces an assessment of STCOL rules and conclusions as to the appropriate rules. While the conclusions reached here may represent only a modest contribution to the literature, the more important offering is the framework for assessment itself—the identification of the questions to be asked and answered.
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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 | 0.028 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.052 |
| Scholarly communication | 0.021 | 0.028 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".