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Record W2620828416 · doi:10.22215/cjers.v11i1.2506

Cutting the Ties? Generational Limitations in Canada’s and Germany’s Citizenship Laws

2017· article· en· W2620828416 on OpenAlexvenueaboutno aff
Martin Weinmann

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipImmigrationGermanEntitlement (fair division)NormativePoliticsState (computer science)LawPoint (geometry)Political scienceSociologyLaw and economicsEconomicsHistoryComputer science

Abstract

fetched live from OpenAlex

This paper compares Canada’s and Germany’s citizenship laws with regard to regulations that delimit the acquisition of citizenship abroad. It finds that the respective regulations are designed similarly, but differ in some details. The Canadian regulation, for instance, prevents citizenship from being passed on to the second generation born abroad, whereas the German rule offers an opportunity to retain citizenship without seriously giving proof of a link to the country. From a normative point of view, there are good reasons to delimit the acquisition of citizenship abroad, but also for an opportunity to retain citizenship if people have a genuine link to the state and its political system. The regulations of each country show deficits in this respect. Thus, this paper suggests introducing requirements for an entitlement to regain citizenship for second or subsequent generations born abroad which could be designed similarly to the requirements for immigrants who want to naturalize. Full text available at: https://doi.org/10.22215/rera.v11i1.254

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)0.007
metaresearch head score (Gemma)0.016
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0120.007
Scholarly communication0.0080.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.116
GPT teacher head0.298
Teacher spread0.182 · 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
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

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of European and Russian StudiesSame topicMigration, Refugees, and IntegrationFrench-language works237,207