FOREIGN AND DOMESTIC EXPERIENCE IN ORGANIZING SETTLEMENT IN HARD-TO-REACH TERRITORIES
Bibliographic record
Abstract
В статье рассматривается проблема освоения труднодоступных территорий, организации на них очаговой и локальной систем расселения и опыт стран, обладающих большими малозаселенными территориями со сложными природно-климатическими условиями, такими как Канада и Австралия. Показаны основные подходы к его организации в этих странах и ключевые характеристики такого расселения. Проведен сравнительный анализ, рассмотрены сходства и отличия этих подходов от существующих методик градостроительного освоения российского Дальнего Востока. The article deals with the problem of the development of hard-to-reach territories of a number of countries, the organization of focal and local settlement systems on them. The experience of countries with large sparsely populated territories with complex natural and climatic conditions, such as Canada and Australia, is attracted. The key characteristics of such settlement, the main approaches to its organization in these countries are shown. A comparative analysis is carried out, the similarities and differences of these approaches to the existing methods of urban development of the Russian Far East are considered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".