Indigenous Rights and Advanced Capitalism in Community Colleges: The Case of Nunavut Arctic College
Bibliographic record
Abstract
The Nunavut Land Claims Agreement (NLCA) between the Inuit in the Nunavut Settlement Area (formerly part of the Northwest Territories) and the Crown of Canada, led to the creation of Nunavut in 1999. A public government in the Inuit homeland, Nunavut has the responsibility to put into effect the Inuit rights and benefits set out in the NLCA as well as provide a wide range of services tailored to the needs of all Nunavummiut of which 85% are Inuit. With a vast and largely untapped mineral, oil, and gas potential, Nunavut is now preparing to a private sector market economy open to global investors in natural resource exploration and exploitation. Certainly, Nunavut is a place where economic development and indigenous rights intersect crosscutting global, national, and territorial boundaries. This chapter looks at how indigenous peoples rights and the imperatives of a globalized/globalizing economy, are projected into and taken up by Nunavut Arctic College, Nunavut's sole postsecondary education institution. Integrating textual and contextual instances of analysis, this chapter highlights how the College translates seemingly conflicting policy messages, into all-encompassing education practices that weave into the omnipresent right to indigenous self-determination.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.046 | 0.021 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".