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Record W2027257909 · doi:10.1080/13621025.2011.534923

The unbearable rightfulness of being human: citizenship, displacement, and the right to not have rights

2011· article· en· W2027257909 on OpenAlexaff
Mark F. N. Franke

Bibliographic record

VenueCitizenship Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsHuman rightsCitizenshipInternational human rights lawFundamental rightsRight to propertyLawPolitical scienceHumanitySociologyUniversality (dynamical systems)Reservation of rightsLaw and economicsPolitics

Abstract

fetched live from OpenAlex

Claims to human rights protection made by displaced persons are displaced from the universe of humanity and rendered ineffective by the geopolitical character of modern international human rights law, in favour of the protection of citizens' rights claims. In response, there is increasing interest in leveraging respect for and protection of the rights of displaced persons through extension of the rights enjoyed and supposedly borne by emplaced citizens. However, it is a mistake to assume that humans as citizens bear human rights or that the freedoms that they may be able to extend beyond state boundaries are universalisable. The extension of the right to citizenship functions to displace questions of human rights themselves. The question of the human in rights is in fact always displaced, as long as the human subject is acted upon as if it could possess rights. In paying attention to the critical perspectives with which displaced persons confront the citizen, she or he may come to appreciate the fact that the universality of human rights is served where one does not claim to have rights but, rather, actively engages, without limits, with others in the struggle for rights and their respect.

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)0.004
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.041
Scholarly communication0.0040.005
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.330
Teacher spread0.273 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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