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Record W2217869628

At the Edge of Law’s Empire: Aboriginal Interraciality, Citizenship, and the Law in British Columbia

2006· article· en· W2217869628 on OpenAlexaffabout
Jean Barman

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCitizenshipMetisLawStatuteEmpireIndigenousPolitical sciencePrejudice (legal term)SociologyHistoryPolitics
DOInot available

Abstract

fetched live from OpenAlex

Aboriginal interraciality has had a distinctive history in British Columbia. The descendants of fur trade and gold rush unions between newcomer men and Aboriginal women have experienced much the same prejudice and discrimination as have members of other groups whose skin tones similarly differ from those of the dominant society. Interracial British Columbians have not, however, been recognized in law as have other groups defined by physical appearance. Unlike their counterparts east of the Rocky Mountains, families originating in fur trade unions did not become legally constituted as Metis. And, unlike Indians across Canada, interracial British Columbians were not reduced through federal statutes to a dependency status. Nor were they deprived of the rights of citizenship, as were members of the principal monoracial minorities in British Columbia. Aboriginal interraciality has, rather, occupied an in between, or liminal, space at the edge of law’s empire in which descendants have enjoyed the forms but not the substance of citizenship. Because Aboriginal interraciality has had no legal status, descendants in British Columbia have had no access to expanding rights for Metis people or to justice to call attention to, or remedy, past wrongs.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.591

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0370.009
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0010.004
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 head0.006
GPT teacher head0.245
Teacher spread0.238 · 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 designQualitative
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

Citations2
Published2006
Admission routes2
Has abstractyes

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