ОПРЕДЕЛЕНИЕ ПЕРСПЕКТИВНЫХ ФИНАНСОВЫХ ЦЕНТРОВ С ПОЗИЦИИ ФУНДАМЕНТАЛЬНЫХ ТЕОРЕТИЧЕСКИХ КОНЦЕПЦИЙ // The Identification of the Perspective Financial Centres Based on Fundamental Theoretical Approaches
Bibliographic record
Abstract
The authors evaluated the middle-term prospects of the development of the international financial centres (IFCs) based on the three theories mentioned in the economic literature: geography of finance, law and finance and the time zone theory. This issue is relevant in particular for developing countries, seeking to diversify their economies, including Russia. The aim of the article is the formation of methodologic tools available to determine the points of the faster growth among the IFCs. Due to the application of the author’s approach it was elucidated that from the standpoint of real GDP growth’s forecast IFCs in Asia-Pacific region have a strong prospects for the further development: Seoul (Korea), Sydney (Australia), Shanghai and Shenzhen (both - China), Kuala Lumpur (Malaysia), Mumbai (India), Jakarta (Indonesia). Based on the “law and finance” theory the favorites are Dublin (Ireland), Vancouver (Canada), Los Angeles (United States) and Doha (Qatar), due to the geographical factor - Dubai (UAE). The authors also concluded that there are no prerequisites for increase the competitiveness of IFC in Moscow in the medium term. In a tense geopolitical situation and the maintenance of the sanction regime against the russian lending institutions the further development of the financial centre in Moscow should be seen as a source of domestic resources for real GDP growth and ensuring the national economic security. В статье проведена оценка потенциала дальнейшего развития международных финансовых центров (далее - МФЦ) в среднесрочной перспективе на основе трех теорий: географии финансов, истоков правовой системы и временных зон. Данный вопрос актуален, прежде всего, для развивающихся стран, стремящихся к диверсификации своей экономики, в том числе и для России. Цель работы - формирование доступного методологического инструментария для определения точек опережающего развития среди МФЦ. По итогам применения авторского подхода установлено, что с позиции прогнозов экономического роста в странах Азиатско-Тихоокеанского региона наибольший потенциал имеют Сеул (Республика Корея), Сидней (Австралия), Шанхай и Шеньчжень (оба - КНР), Куала-Лумпур (Малайзия), Мумбаи (Индия), Джакарта (Индонезия). На основе концепции истоков норм права наибольшие шансы у МФЦ в Дублине (Ирландия), Ванкувере (Канада), Лос-Анджелесе (США) и Дохе (Катар), по географическому фактору - у Дубая (ОАЭ). Cделан вывод, что отечественный МФЦ не имеет предпосылок для повышения конкурентоспособности в среднесрочной перспективе. По мнению авторов, в условиях напряженной геополитической обстановки и сохранения санкционного режима в отношении российских кредитных учреждений развитие финансового центра в Москве следует рассматривать как источник внутренних ресурсов для обеспечения роста реального ВВП и национальной экономической безопасности.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".