Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter examines the role and extent of the powers of the ‘registrar’ under automated Torrens systems such as those in New Zealand, Australia and Canada. Judicial interpretations of these powers both prior to, and following, Frazer v Walker is reviewed. This analysis demonstrates that notwithstanding the comment of the Privy Council in that case that the registrar’s powers are ‘broad and extensive’, the feared erosion of indefeasibility through a more liberal exercise of those powers has not occurred. The changes that were introduced in New Zealand under the Land Transfer Act 2017 to clarify and constrain the extent of the registrar’s powers in that jurisdiction are examined in detail in this context. The chapter also explores the impacts of automation and digitalisation of land registration and conveyancing processes on the appropriate role and extent of the registrar’s powers. A further focus is the privatisation, or part privatisation, of land registration systems that has already occurred in some Canadian provinces and Australian states, and is being actively considered in a number of other jurisdictions. This raises important questions relating to security of title and integrity of the land registration system, including the continued need for, and shape of, government oversight through a public office or agency such as the registrar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it