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Record W2741567171

Citizen Supplicants?: Alain Carins' Citizens Plus and the Politics of Aboriginal/Constitutional Scholarship

2002· article· en· W2741567171 on OpenAlexaboutno aff
Alexandra Dobrowolsky, Richard Devlin

Bibliographic record

VenueRevue d'études constitutionnelles · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyPoliticsScholarshipHumanitiesPolitical scienceContext (archaeology)ElaborationSociologyEthnologyLawPhilosophyGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

espanolL’ouvrage d’Alan Cairns intitule Citizens Plus fut d’emblee considere comme une contribution tres importante concernant la question autochtone au Canada. Les auteurs defendent trois theses concernant cet ouvrage: d’abord, que la vision proposee par Alan Cairns sur les Autochtones doit etre situee dans le contexte plus general de son oeuvre; que la reconnaissance des droits des Autochtones a la difference reste limitee; enfin, que le projet de ‘citoyen plus’ necessite une plus grande elaboration. EnglishAlan Cairns’ Citizens Plus is a significant intervention in the debate on Aboriginal rights that merits careful consideration. The authors advance three basic claims. First, Citizens Plus can only be fully appreciated when read in the context of Cairns’ larger constitutional vision. Second, while there is much to be celebrated in Citizens Plus, because of Cairns’ commitment to an ideology of “oneness” he is unable to provide a thick recognition of Aboriginal difference within the Canadian constitutional regime. Third, to be persuasive, the idea of “citizens plus” will require further elaboration, because in its current form Aboriginal peoples look more like citizens supplicant.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.458
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.028
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.298
Teacher spread0.260 · 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

Citations4
Published2002
Admission routes1
Has abstractyes

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