MétaCan
Menu
Back to cohort
Record W2737459881 · doi:10.1515/til-2017-0013

Property and Sovereignty: How to Tell the Difference

2017· article· en· W2737459881 on OpenAlexaff
Arthur Ripstein

Bibliographic record

VenueTheoretical Inquiries in Law · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicProperty Rights and Legal Doctrine
Canadian institutionsMuscular Dystrophy CanadaUniversity of Toronto
Fundersnot available
KeywordsSovereigntyConfusionProperty (philosophy)Law and economicsScope (computer science)PoliticsStewardship (theology)State (computer science)Political scienceLawSociologyEpistemologyPhilosophyPsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract Property and sovereignty are often used as models for each other. Landowners are sometimes described as sovereign, the state’s territory sometimes described as its property. Both property and sovereignty involve authority relations: both an owner and a sovereign get to tell others what to do — at least within the scope of their ownership or sovereignty. My aim in this Article is to distinguish property and sovereignty from each other by focusing on what lies within the scope of each. I argue that much confusion and more than a little mischief occurs when they are assimilated to each other. The confusion can arise in both directions, either by supposing that property is a sort of stewardship, or that sovereignty is a large-scale form of ownership. One of the great achievements of modern (i.e., Kantian) political thought is recognizing the difference between them.

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)0.016
metaresearch head score (Gemma)0.061
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 score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0050.060
Scholarly communication0.0120.044
Open science0.0030.009
Research integrity0.0090.014
Insufficient payload (model declined to judge)0.0150.002

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 head0.045
GPT teacher head0.327
Teacher spread0.283 · 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

Citations46
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTheoretical Inquiries in LawSame topicProperty Rights and Legal DoctrineFrench-language works237,207