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Record W2781774145 · doi:10.29173/alr1441

A Primer on Citizenship Revocation for WWII Collaboration: The 1998-1999 Federal Court Term

2000· article· en· W2781774145 on OpenAlexvenueno aff
Claire I. Farid

Bibliographic record

VenueAlberta Law Review · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsLawJurisprudenceCitizenshipPolitical scienceAppealLegislationDutyImmigrationSociologyPolitics

Abstract

fetched live from OpenAlex

This article provides a review of recent jurisprudence in relation to revocation of citizenship proceedings against those alleged to have committed war crimes or crimes against humanity. The author discusses proceedings involving citizenship obtained by deception by those involved in World War II, with a particular focus on five cases decided in late 1998 and 1999. The article addresses both procedural and substantive issues that have arisen in these proceedings. Although past procedural problems of characterization of the proceedings, the scope of required notices, and rights to appeal have generally been clarified in recent jurisprudence, some specific problems still remain to be resolved. The author points out that the substantive issues surrounding collaboration, actual post-WW Il security screening practices, the existence of a duty of candour, and the legal authority for security screening of immigration applicants still remain in a state of uncertainty as the current cases have provided conflicting results. Interpretation of old legislation and the determination of how such legislation was actually applied to security screening by immigration officials at the time of the immigrant's application are the main concerns in deciding these substantive issues. Matters are further complicated by the lack of evidence, both testimonial and documentary. The resolution, or lack thereof, of the procedural and substantive issues will have a bearing on proceedings initiated by the government in relation to modern war crimes cases.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.336
Teacher spread0.308 · 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.

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

Citations3
Published2000
Admission routes1
Has abstractyes

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