Foreign experience of state financial support of Arctic territories (on the example of the northern territories of Canada)
Bibliographic record
Abstract
Настоящая статья посвящена исследованию зарубежного опыта государственной финансовой поддержки по развитию арктических территорий (на примере северных территорий Канады). Актуальность исследования заключается в рассмотрении государственной политики по освоению и развитию Арктики зарубежных стран. Основной целью статьи является необходимость изучения зарубежного опыта финансового обеспечения для устойчивого развития арктических территорий Канады. Основная задача заключается в освещении инструмента финансового регулирования развития северных территорий Канады. В заключении делается вывод о наличии программно-целевых инструментов и системы финансового выравнивания на основе межбюджетных трансфертов, применяемыми правительством Канады для развития северных территорий. This article is devoted to a research of foreign experience of state financial support for the development of Arctic territories (for example, the northern territories of Canada). The relevance of the research lies in the consideration of the state policy on the development and development of the Arctic of foreign countries. The main goal of the article is the need to study foreign experience of financial support for the sustainable development of the Arctic territories of Canada. The main objective is to highlight the instrument of financial regulation of the development of the northern territories of Canada. In conclusion, it is concluded that there are program-targeted tools and a system of fi nancial equalization based on inter-budget transfers used by the Government of Canada for the development of the northern territories.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".