Indigenous energy diplomacy in the Arctic : Probing the complexity with cases in Sámpi and the Inuvialuit region
Bibliographic record
Abstract
“Indigenous energy diplomacy” is a relatively new term, but Indigenous peoples have long practiced various forms and degrees of traditional kinship diplomacies as well as more recently engaged in mainstream diplomacy in global politics and international relations on issues related to energy and in particular, energy resources Indigenous energy diplomacy within the Arctic region. Energy diplomacy is a complex practice that differs among Arctic Indigenous peoples, such as the Sámi and Inuit energy diplomacies in the current context of energy crisis and energy resource conflict. Makere Stewart-Harawira stresses the importance of integrating Indigenous philosophies and worldviews into contemporary Indigenous diplomacy. She observes a shift in the focus of Indigenous self-determination from political status to economic development, influenced by neoliberal economic ideologies and neoconservative politics (Stewart-Harawira 2009, 209). This talk will consider the two modes proposed by Stewart-Harawira, of placing Indigenous ontologies at the center of their diplomacies on the one hand, and of reinscribing Indigenous self-determination as economic development, to illustrate the diverse landscape of contemporary Indigenous energy diplomacy. The specific focus is on Sámi reindeer herding in Norway vis-à-vis wind industry and the energy security development in the Inuvialuit settlement region in the Northwest Territories, Canada.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".