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Record W7143623741 · doi:10.15020/00002320

The Lost Canadians’ Lost Citizenship and Nationality : How Legislation Deprived and Restored Them

2022· article· ja· W7143623741 on OpenAlexaboutno aff
健司 鈴木, Kenji Suzuki

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2022
Typearticle
Languageja
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipLegislationNationalityCharterImmigrationAssertion

Abstract

fetched live from OpenAlex

The Canadian Citizenship Act of 1946, the first legislation on Canadian citizenship, enforced on January 1, 1947, provided the conditions and the requirements for being Canadian, which varied by the birth date, birthplace, and parents’ nationality and marital status. The Citizenship Act of 1976, succeeding the Act of 1946, partly eased the eligibility conditions for citizenship. However, this new legislation did not apply retroactively to persons whose citizenship had already been voided; it created another division in the applicable scope of the regulation before and after its enforcement. These acts deprived many people who believed themselves Canadian of Canadian citizenship or the right to it. Until Bill C-37 came into effect in 2009 to amend the Citizenship Act, an estimated 70 thousand people failed to obtain Canadian citizenship or ceased to be Canadian citizens unknowingly due to the complicated regulations for retaining citizenship. They are called the Lost Canadians. The previous legislation included many discriminatory provisions infringing the principles of equality and due process guaranteed by the Canadian Charter of Rights and Freedoms. Court judgments on these matters provided legal grounds for the Lost Canadians’ assertion and led to the comprehensive review of the citizenship acts in the legislature.

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)0.010
metaresearch head score (Gemma)0.034
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: none
Teacher disagreement score0.117
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.034
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0490.030
Scholarly communication0.0210.010
Open science0.0040.013
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0120.001

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 head0.028
GPT teacher head0.237
Teacher spread0.209 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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