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The Relativity of Title and Causa Possessionis

2013· book-chapter· en· W94463204 on OpenAlexaff
Larissa Katz

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPossession (linguistics)DominionVariety (cybernetics)Law and economicsNormativeLawPolitical scienceNexus (standard)Property (philosophy)SociologyEpistemologyPhilosophyEngineeringComputer scienceLinguistics

Abstract

fetched live from OpenAlex

This chapter argues that possession should not function as the linchpin of property at all. Instead, ownership combined with privity, force, and fraud get us what the relativity of title and its emphasis on possession are sometimes thought to provide. The chapter is organized into two parts. The first considers the special importance of the role of true owners in possessory disputes. It emphasizes the concept of ownership pro tem, which preserves the authority of owners by enabling a finder to slot herself into a role that is protective of the office of ownership. This concept of ownership pro tem does not, however, explain all the variety of rights to possess in the common law. Not all holders of rights to possess are owners pro tem. Someone who mistakenly assumes something is hers and someone who knows it is not but who asserts dominion over it anyway — i.e., a thief — both possess without deference to the authority of the true owner. What explains this other variety of right to possess, that of the wrongdoer? The second part argues that there is a second and distinct normative nexus that exists between a wrongdoer and a later possessor in some contexts. The ancient concept of privity explains this normative nexus.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.018
Scholarly communication0.0070.015
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0100.003

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.

Opus teacher head0.030
GPT teacher head0.245
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2013
Admission routes1
Has abstractyes

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