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Record W4386687408 · doi:10.1017/s175297192300012x

Property and international relations: lessons from Locke on anarchy and sovereignty

2023· article· en· W4386687408 on OpenAlexaff
Nancy Bertoldi

Bibliographic record

VenueInternational Theory · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSovereigntyNormativeInternational relationsLaw and economicsProperty (philosophy)LawSociologyPolitical sciencePhilosophyEpistemologyPolitics

Abstract

fetched live from OpenAlex

Abstract Property has a ubiquitous presence in international practice, but its implications for theorizing world order are not adequately explored. I remedy this by showing how property constitutes the core concepts of anarchy and sovereignty in international relations (IR) as overlapping spaces of right-based governance. I develop my account of a property-based world order in relation to the work of John Locke. Locke is generally overlooked as a core IR thinker, with the unfortunate consequence that anarchy and sovereignty are conceptualized as polar opposites under the enduring shadow of Hobbes. Even prominent critics of Hobbesian anarchy rely on Hobbesian notions of sovereignty, resulting in minimalist conceptions of international society and international ethics. To counter these Hobbesian legacies, I turn to Locke's limited, plural, and fluid accounts of anarchy and sovereignty and show how they are grounded in a normative notion of property that mutually constitutes them. This provides an alternative to the Hobbesian absolutist conceptions of anarchy and sovereignty that many IR theorists still operate with. The result is a distinctly normative vision for IR that condemns the twin evils of conquest and tyranny.

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)0.008
metaresearch head score (Gemma)0.009
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 score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.055
Scholarly communication0.0100.016
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.118
GPT teacher head0.397
Teacher spread0.278 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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