Арктическая урбанизация: феномен и сравнительный анализ
Bibliographic record
Abstract
The article provides a comparative assessment of the level of urbanization within the Arctic territories of the world according to common criteria. All settlements of the Arctic with population exceeding 5,000 people are analyzed, regardless of their status. The border of the Arctic coincides with the southernmost of three options most often used in the international studies on the socio-economic geography of the Arctic. According to the results of the assessment, the level of urbanization in many regions of foreign Arctic is lower than the estimates given in relevant scientific literature. Specific features of the development of Arctic cities are considered, the main types of cities in the Russian and foreign Arctic are identified. While choosing the typology criteria, the following factors were taken into account: the influence of remoteness from other urban centers on the economic development (the importance of this factor is high in the Arctic due to the rare urban network); factors of socio-economic development in the «knowledge economy» era; transport and geographical location etc. As a result, three main criteria were chosen, i. e. the presence of its own university, administrative status, location within the agglomeration of a larger city. Four types of Arctic cities were identified: 1. Key multifunctional (university) cities. 2 Peripheral administration centers. 3. Suburban cities of different specializations. 4. Remote industrial centers. The criterion of coastal position was used to distinguish subtypes. As a rule, cities of the first type have the status of a national or regional administrative capital (with some exceptions), and are university cities. Almost half of the urban population of the Arctic lives in such cities (Murmansk, Arkhangelsk, Anchorage, Tromso, Reykjavik, etc.). The second type includes regional capitals without their own university (Salekhard, Yellowknife, etc.). The cities of the third type are mainly concentrated around the cities of the first type (Murmashi, Wasilla, etc.). Finally, the fourth type of cities embraces remote cities that do not have either capital status or an independent university. This group includes mainly cities located near the mineral deposits (Novy Urengoy, Labrador City, etc.). The specific feature of the Russian Arctic is a higher proportion of inland (non-port) suburban cities (most rapidly losing population) and remote industrial centers (conditionally «cities near deposits»). The foreign Arctic has a high proportion of the cities of the first type (capital university cities).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".