Bibliographic record
Abstract
Indigenous members of the Canadian Forces (CF) are an integral part of the organization, working and fighting alongside their non-Indigenous colleagues all over the world. As a non-combative sub-set of the CF, however, the Canadian Rangers are a unique branch of the Reserves that are without compare. Functioning primarily for their communities, the Rangers represent the potential for the CF to effectively work with Indigenous communities and culture, while maintaining CF operational objectives in the Arctic. This article explores how the Rangers balance the sovereignty of their communities with the aims of the CF by integrating Indigenous cultures, language, and ways of knowing into their operational and capabilities, while remaining semi-autonomous from the CF culture and hierarchy. This article concludes that while the Rangers are an example of the potential for Indigenous and Canadian partnerships, there is also an alarming disparity and inequitable access to secure full-time employment and healthcare. Moreover, Rangers face many of the same issues as those in the communities they strive to serve. Therefore, this article argues that if Canada is serious about reconciliation and creating more opportunities for Indigenous persons in the Arctic, then part of that aim should also include providing the Rangers with the same support other areas of the CF are privileged to receive.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.036 | 0.026 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".