The OAS Model Law on Secured Transactions: A Comparative Analysis
Bibliographic record
Abstract
The 21st Century began as it ended, with an ongoing struggle to allow the poor of the world to partake in the prosperity of market economics. This article focuses on legal reforms to the law of secured transactions in Latin America, a part of the world where small and medium sized merchants have no meaningful access to credit. It discusses the OAS Model Law on Secured Transactions of 2002, a law inspired by Article 9 of the Uniform Commercial Code and the Canadian Personal Property Security Acts as well as by Civil Law institutions traceable to classical Roman Law and more recently to early twentieth century German judicial decisions. The successful blend of these sources was made possible by a set of guiding principles to the OAS Model law drafted at the National Law Center for Inter-American Free Trade. These principles guided but only partially Mexico's statutory amendments of 2000 and 2003, they are also guiding more fully and effectively present legislative efforts in Central America. This article compares selected provisions of the OAS Model Law to those in UCC Article 9 as well as in Mexico's statutory amendments. It concludes that despite the very significant changes effectuated in Mexican law more changes are in order. This is particularly true in light of the major improvements in the availability of commercial and consumer credit experienced by Mexico with the enactment of only partially effective statutory changes in 2000 and 2003.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".