Locating Indigenous Agencies in Climate Policies of the Arctic : Positionalities of Indigenous People(s) and Traditional Knowledge in the Science-Policy Discourse of Climate Change
Bibliographic record
Abstract
Indigenous people in the Arctic are recognized as being on front line of confronting the effects of changing climate as well as of the global measures taken for its management, however, remaining marginalized under the conventional ways of governing. This thesis examines the positionalities of indigenous people(s) and traditional knowledge in the science-policy discourse of climate change. Three separate discursive platforms will be examined with the understanding that all actors fill the domain with meaning. Focus on the regional area of the Arctic is constructed through case studies of the Sámi in Finland and the Inuit in the Kingdom of Denmark. The theoretical framework draws from the post-structural debate on agency and structure and is further connected to the Neo-Gramscian concept of hegemony. Through this International relations theorization, power distributional aspects of climate governance are presented, and the domination of the western scientific framework (IPCC) is questioned. Post-colonialism is utilized to highlight the unwished potential of reinforcing outcomes of western and non-western oppositionalities. By utilizing post-structural discourse analysis with a Foucauldian understanding of discourse, this thesis concludes that both indigenous peoples and their intellectual contribution remain constructed around recognition under the framework of western institutionalism.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".