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Record W2266251546

The Securitization of Dual Citizenship

2007· article· en· W2266251546 on OpenAlexaff
Audrey Macklin

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitizenshipSecuritizationPolitical scienceNational securityState (computer science)PopulationLaw and economicsImmigrationLawSociologyBusinessPolitics
DOInot available

Abstract

fetched live from OpenAlex

The securitization of immigration prioritizes the goal of protecting the body politic from infection by the menacing foreigner. The securitization of legal citizenship complements this process by facilitating the discursive and sometimes literal mutation of the citizen into the foreigner. Investing in mechanisms that enable the conversion or reversion of risky people to the legal status of foreigner simplifies the equation of state security with citizen security. Ordinarily, an elision of national security with citizen security founders on the realization that a state's pursuit of the former almost invariably involves individual rights violations that jeopardize the latter. However, if a population can be persuaded that alleged security risks are or ought to be regarded as essentially 'foreign', then it becomes easier to promote what is done in the name of state security as coeval and consonant with advancing citizen security. This trend carries with it certain implications for discourses and practices of dual citizenship in western industrialized states. I contend that the securitization of citizenship operates by making acquisition of a second citizenship less attainable for refugees and other forced migrants and, paradoxically, by making birthright citizenship itself less secure for certain members of diasporic communities who already possess dual nationality.

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)0.015
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.306
Teacher spread0.293 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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