The Abandoned Ones: Non-Status Indians and Political Organizing
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.051 | 0.047 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".