Greg Taylor, The Law of the Land: The Advent of the Torrens System\nin Canada
Bibliographic record
Abstract
In the fall of 1980 Charles W. MacIntosh, Q.C., then the head of the Land Registration and Information Service (L.R.I.S.), a federally funded initiative of the Council of Maritime Premiers, delivered a lecture to first year students at Dalhousie Law School. He announced with justifiable pride that Nova Scotia had enacted the Land Titles Act' and that the province would be moving to a Torrens system of title registration. The time for throwing off the centuries-old system ofdeeds registration, where the government provided a passive repository for title documents, was nigh! Nova Scotia would come to enjoy the benefits of a Torrens system of title registration, where land is indexed by location rather than by an interest holder's name. A government guarantee of parcel ownership would replace title certification based on lawyers' opinions. Expensive and repetitive historic title searches would become a thing of the past in Nova Scotia!
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 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".