MétaCan
Menu
Back to cohort
Record W3043080976 · doi:10.3138/utlj-2020-0031

The office of ownership revisited

2020· article· en· W3043080976 on OpenAlexaffvenue
Christopher Essert

Bibliographic record

VenueUniversity of Toronto Law Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCovenantProperty (philosophy)EasementLaw and economicsBusinessProperty rightsLawPolitical scienceSociologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

In this article, I revisit the arguments in, and address some concerns about, an earlier article of mine, ‘The Office of Ownership.’ This article makes two main points. The first is about the ways in which a transfer of property from one person to another affects the obligations of third parties. I continue to defend the earlier article’s claim that, by thinking about the obligations owed to owners of property as being owed to ‘the owner,’ rather than to the particular named person who happens to be the owner, we can maintain both the idea that property rights are in rem and the idea that they partake of private law’s distinctive bilateral normativity. The second is about the extent to which the notion of an office is helpful in thinking about ownership. There is reason to doubt that it is, notably because owners’ powers are typically not bounded in the way that office-holders’ powers seem to be. But I argue that, at least some of the time, particularly in contexts where owners are able to exercise powers that bind their successors in title, such as by creating easements, leases, or running covenants, the powers of ownership do seem bounded by their purpose.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.256
Teacher spread0.227 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of Toronto Law JournalSame topicLegal principles and applicationsFrench-language works237,207