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Record W2767591425 · doi:10.1017/s0003055417000442

Democratic Citizenship and Denationalization

2017· article· en· W2767591425 on OpenAlexaff
Patti Tamara Lenard

Bibliographic record

VenueAmerican Political Science Review · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicWar, Ethics, and Justification
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDemocracyCitizenshipPolitical scienceState (computer science)PoliticsLawLaw and economicsTerrorismPower (physics)Sociology

Abstract

fetched live from OpenAlex

Are democratic states permitted to denationalize citizens, in particular those whom they believe pose dangers to the physical safety of others? In this article, I argue that they are not. The power to denationalize citizens—that is, to revoke citizenship—is one that many states have historically claimed for themselves, but which has largely been in disuse in the last several decades. Recent terrorist events have, however, prompted scholars and political actors to reconsider the role that denationalization can and perhaps should play in democratic states, in particular with respect to its role in protecting national security and in supporting the global fight against terror more generally. In this article, my objective is to show that denationalization laws have no place in democratic states. To understand why, I propose examining the foundations of the right of citizenship, which lie, I shall argue, in the very strong interests that individuals have in security of residence. I use this formulation of the right to respond to two broad clusters of arguments: (1) those that claim that it is justifiable to denationalize citizens who threaten to undermine the safety of citizens in a democratic state or the ability of a democratic state to function as a democratic state, and (2) those that claim that it is justifiable to denationalize dual citizens because they possess citizenship status in a second country that is also able to protect their rights.

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)0.012
metaresearch head score (Gemma)0.018
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 score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.042
Scholarly communication0.0050.006
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.364
Teacher spread0.267 · 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

Citations96
Published2017
Admission routes1
Has abstractyes

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