Trends and Effects of Climate Change on Reindeer Husbandry in the Republic of Sakha (Yakutia)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it