Trends and Effects of Climate Change on Reindeer Husbandry in the Republic of Sakha (Yakutia)
Bibliographic record
Abstract
Abstract The Republic of Sakha (Yakutia), like other Arctic regions, faces severe climatic and environmental changes and hazards such as temperature increase, permafrost thaw, intense forest fires, earlier melting, and flooding. Significant climate and environmental changes over the past decades pose risks to the preservation of the traditional way of life of Indigenous peoples, including reindeer husbandry. Understanding trends and effects of climate change in the Republic of Sakha is needed to project and manage the future of reindeer husbandry, the resilience of Indigenous communities, and plan their economic adaptation. In this article, we analyze meteorological data from four weather stations located in different reindeer herding areas of Yakutia focusing on snow cover formation, permafrost conditions, and forest fires; provide the results of in-depth interviews with local people on the impact of climate change on reindeer herding. The financing of resilience development in the Republic is discussed. In conclusion, suggest necessary measures that can be taken for adaptation and overcoming emerging threats and challenges for further development of reindeer husbandry which is the central basis of the identity of the Indigenous peoples of the North.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".