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Record W2284807334 · doi:10.4337/9781781001844.00027

What makes a good law of security?

2015· book-chapter· en· W2284807334 on OpenAlexaboutno aff
Richard Calnan

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)LawLegislationFlexibility (engineering)CommissionSecurity interestPersonal propertyGovernment (linguistics)BusinessLaw reformPolitical scienceLaw and economicsProperty (philosophy)EconomicsManagement

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.302
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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