Book Review of the Law of the Land: The Advent of the Torrens System in Canada, by Greg Taylor (Toronto: Osgoode Society for Canadian Legal History, 2008)
Bibliographic record
Abstract
Systems for recording interests in land are not the subject of much public interest or concern in Canada. Occasionally a sympathetic victim of egregious fraud receives some media attention, but generally the land system operates quietly in the background. This has not always been so, and Greg Taylor's history of Torrens or title registration in Canada reveals a nineteenth century during which the merits and limitations of the common law, deeds registration, and title registration systems were vigorously and publicly debated. Eventually, title registration based on a model first developed in South Australia would prevail in the provinces and territories from British Columbia to Ontario. The civil law jurisdiction of Quebec remains an outlier, and the conversion of the Maritime Provinces to title registration is occurring unevenly, but otherwise Canada, unlike its neighbour to the south which opted for deeds registration systems and title insurance, is a collection of title registration jurisdictions. Taylor’s book, one of only a handful of single-authored national legal histories in Canada, reveals how this came to be so.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".