Human security of Inuit and Sámi in Canada and Finland: comparing Arctic policies
Bibliographic record
Abstract
The 21st century looks like the century of climate change threat due to inaction of states, governments in the past. Not that there were not calls and studies alerting to the situation we are witnessing. Arctic Indigenous peoples were the first to feel the causeeffect, with no responsibility to the harm that was and is affecting their way of life, their living subsistence, their home. Climate change has direct and indirect impacts. Facing the inability of the States to keep them safe and secure, Inuit and Sámi organisations had to take the lead to protect themselves, at least with their voices heard at international level. The Inuit Circumpolar Council and Sámi Council have done a great job that allowed to recognise their human rights as well as giving them a place at the Arctic Council as Permanent Participants. In order to understand the difficulties at national level, the comparison work will be helpful to analyse the applicability of human security (within a trinity that includes Green theory and ecosystem approach) of Canada and Finland´s Arctic policies, where Inuit and Sámi live, respectively, acknowledging the impact both countries can provide to their Arctic communities as part of their country and society, accepting their diversity. Keeping population safe is an obligation of States, though in this new century and climate threat context, they can not to do it alone.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".