Impact of the COVID-19 pandemic on labor markets of Arctic territories of circumpolar countries.
Bibliographic record
Abstract
The COVID-19 pandemic has threatened human safety and well-being, has outlined new requirements for the functioning of sectors of the economy and social sphere that directly determine the conditions of life, and has required timely comprehension of the COVID-19 pandemic consequences as part of updating the measures of social and economic support. Assessing the impact of the current crisis situation caused by the COVID-19 pandemic on the labor markets of circumpolar countries was the purpose of this study. The objectives of the study included an analysis of the effects of the COVID-19 pandemic on the economies of circumpolar countries, an analysis of governmental measures to mitigate the socio-economic consequences of the COVID-19 pandemic, an analysis of employment and unemployment rates in 2019–2020, and a rationale for the role of government in reducing social tensions in Arctic labor markets. The labor markets of regions whose territories are fully attributed to the Russian Arctic, as well as labor markets of the Arctic territories of Canada, the United States, Norway, Finland and Sweden were the object of this study. As a result of the study, it was determined that the greatest decline was observed in consumer demand-oriented sectors of the economy. It has been revealed that the labor markets have been negatively affected by the decline in the number of small and medium-sized businesses and individual entrepreneurs. The scientific novelty of the study is determined by a special assessment of the cumulative impact of the COVID-19 pandemic and governmental measures to limit its spread on employment and unemployment indicators that identify trends in Arctic labor markets. The practical significance of the study lies in the fact that its main conclusions are aimed at updating the measures of employment regulation in the labor markets of the Russian Arctic. The prospects for further research are determined by the long-term nature of the consequences of the COVID-19 pandemic for the Arctic economies and the formation of appropriate proposals and recommendations for adapting labor markets in the Russian Arctic to the emerging situation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".