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Record W3121435987 · doi:10.1177/0090591707299808

Citizenship as Inherited Property

2007· article· en· W3121435987 on OpenAlexaff
Ran Hirschl, Ayelet Shachar

Bibliographic record

VenueTSpace · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoliticsLaw and economicsCitizenshipScrutinyProperty (philosophy)RealmProperty rightsSociologyAnalogyInheritance (genetic algorithm)State (computer science)LawPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The global distributive implications of automatically allocating political membership according to territoriality (jus soli) and parentage (jus sanguinis) principles have largely escaped critical scrutiny. This article begins to address this considerable gap. Securing membership status in a given state or region - with its specific level of wealth, degree of stability, and human rights record - is a crucial factor in the determination of life chances. However, birthright entitlements still dominate both our imagination and our laws in the allotment of political membership to a given state. In this article we explore the striking conceptual and legal similarities between intergenerational transfers of citizenship and property. The analogy between inherited citizenship and the intergenerational transfer of property allows us to use existing qualifications found in the realm of inheritance as a model for imposing restrictions on the unlimited and perpetual transmission of membership with the aim of ameliorating its most glaring opportunity inequalities.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.023
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.002
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 head0.112
GPT teacher head0.443
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations107
Published2007
Admission routes1
Has abstractyes

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