1 Legal Bilingual and Bisystemic Dictionary of Property in Canada
Bibliographic record
Abstract
Abstract: The Legal Dictionary of Property in Canada (LDPC) is an interpretative bilingual and bisystemic encoding and decoding tool for Canadian legal texts and notably, for legislative and judicial texts dealing with federal law. It was created to address this specific need. By bilingual we mean both of Canada’s official languages, French and English; by bisystemic we refer to the legal systems in private law matters, Civil Law and Common Law, which coexist within the Canadian federal law. The dictionary’s theme is property, and the observation of this phenomenon was conducted through the use of an aligned and bilingual corpus of judicial decisions, mostly originating from the Supreme Court of Canada and, to a lesser extent, the New Brunswick Court of Appeal. Its definitions form a set of necessary and sufficient conditions whose specific consistency constitutes an ontology. As a working hypothesis, its validity is therefore verified according to whether the coverage of the observed field is ∗ Editor and Co-Author of the Legal Dictionary of Property in Canada (LDPC) with Anne Des Ormeaux. I would like to offer my thanks and gratitude to Isabelle Palad for the complete revision and layout formatting of this paper, as well as its translation and adaptation into English. Many thanks to Anne Des
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".