Bibliographic record
Abstract
Since the turn of the century, there has been a great deal of discussion in England about the reform of the law of security. It all started in a fairly low-key way. What was proposed was to update the law concerning the registration of company charges as part of the general overhaul of the companies legislation. The Law Commission then got involved, and it produced three papers between 2002 and 2005. Its initial recommendation was to adopt a Personal Property Security Act (PPSA) on the lines of that in Canada and New Zealand, and which has since been adopted in Australia. That recommendation was never adopted. Instead, the government reverted to the initial idea of updating the registration of company charges, and that resulted in a new streamlined registration system in April 2013. Where does that leave the more general reform of the law of security? The purpose of the chapter is three-fold: first, to explore in detail the principles which underlie the approach to the law of security, namely simplicity, flexibility, freedom of contract, and transparency; secondly, to discuss the extent to which the English law of security complies with those principles; and thirdly, to describe briefly how a good law of security might be structured.
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.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".