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Record W2144650553 · doi:10.5663/aps.v3i3.22226

The Abandoned Ones: Non-Status Indians and Political Organizing

2014· article· en· W2144650553 on OpenAlexaffvenueabout
David Newhouse, Yale D. Belanger, Pamela Ouart

Bibliographic record

Venueaboriginal policy studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of LethbridgeTrent UniversityUniversity of Alberta
Fundersnot available
KeywordsPoliticsTreatyPolitical scienceSeverancePublic administrationSociologyLaw

Abstract

fetched live from OpenAlex

This paper explores contemporary issues facing Non-Status Indians in Canada, and their struggles to politically organize in particular. Using James Scott’s theoretical position that political states attempt to create legible populations in order to administer them more easily, this paper examines the category of “Non-Status Indians” and the impacts of federal policy making on their ability to organize. The National Indian Council (NIC), established in 1961, originally articulated the concept of Non-Status Indians as a category of Aboriginal people. Internal pressures led the NIC to split into two groups in 1968: the National Indian Brotherhood, representing status and Treaty Indians; and the Native Council of Canada (NCC), representing Métis and Non-Status Indians. A second severance occurred in 1983 when the Métis National Council split from the NCC, after which the Council for Aboriginal Peoples (CAP) emerged to represent Non-Status Indians and urban Aboriginal peoples. During this period, public policy makers, Status Indians, and Métis literally abandoned the Non-Status label. During the opening decade of the twenty-first century, Non-Status Indian organizations have emerged as new players on the Aboriginal policy landscape. This paper explores this phenomenon, based upon key informant interviews with Non-Status Indian leaders conducted specifically for this project.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.998

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 studies0.0120.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.375
Teacher spread0.360 · 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
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
Published2014
Admission routes3
Has abstractyes

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