The Nature and Diversity of Personal Property Security Systems in Canada
Bibliographic record
Abstract
In Canada, there are three natural groupings of personal property security systems. These are the Common law systems of nine provinces and two territories, the Civil law system of Québec and the Canadian federal legislation relevant to secured lending. The Common law jurisdictions subdivide into two groups consisting of those which have adopted or are about to adopt unitary personal property security legislation modelled upon Article 9 of the U.C.C. of the United States, and those which have not and are not about to adopt such legislation. The purpose of this paper is to describe the common and disparate features of the systems for security on personal or moveable property in Canada. The descriptive exercise indicates that it is impossible to characterize the law in this domain as either completely divergent or homogeneous and that, despite similarities and differences, there is a substantial degree of commensurability among Canadian systems of security on personal property.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".