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Record W3123990262 · doi:10.60082/2817-5069.3144

A Market for Sovereignty? The Roles of Other States in Self-Determination

2017· article· en· W3123990262 on OpenAlexaffvenue
Karen Knop

Bibliographic record

VenueOsgoode Hall law journal · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSovereigntySecessionExpropriationPrerogativePolitical scienceLawInternational lawState (computer science)Self-determinationLaw and economicsIndependence (probability theory)FederalismEconomics

Abstract

fetched live from OpenAlex

How can the popular sovereignty associated with international law’s regulation of self-determination (secession) be reconciled with the state’s traditional property-like prerogative to transfer (cede) territory regardless of the inhabitants’ wishes? Joseph Blocher and Mitu Gulati innovatively propose a “market” for sovereignty that would treat secession more like a sale of property, and cession, less. Existing international law does not conceive of states as potential bidders, buyers, backers, underwriters or investors in a people’s exercise of self-determination. However, international lawyers should not overestimate the differences with Blocher and Gulati’s unconventional proposal. Compared to their idea of market-generated options for sovereignty, the generation of options pursuant to a right of self-determination appears murky in international law. Questions about the rights and duties of other states and the limits on outside investment in a people’s independence were legally salient in colonial self-determination—a doctrinal category of self-determination that Blocher and Gulati neglect. These questions deserve renewed attention in any analytical and critical stock-taking of self-determination in international law.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.231
Teacher spread0.218 · 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 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
Published2017
Admission routes2
Has abstractyes

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