Economic and Geopolitical influence of India through BRICS summit: A brief analysis
Bibliographic record
Abstract
Recently, developing economies have emerged as regional and global growth players due to higher economic integration, regional collaboration, and international trade growth than developed economies. BRICS comprises the five emerging global powers: Brazil, Russia, India, China, and South Africa from Asia, Africa, and Latin America. This bloc incrementally enhances their global engagements in international trade and regional integration through economic collaboration and mutual discussions among different summit levels. BRICS produces around 23 percent of the worldwide merchandise output, and 18 percent of global goods and service trade among 42 percent of the worldwide population. This research work observed that over the last ten years, the weight of the BRICS countries, especially the GDP of China, was growing faster, resulting in a global economic impact on fiscal and monetary policy. In the future, these economies will be more significant in economic integration through trade and FDI movement than the G-7 region, consisting of Canada, Japan, the United Kingdom, France, the United States, Germany, and Italy.BRICS economy remains heterogeneous due to its character, with significant changes in socio, political, and legal frameworks. The nominal GDP of BRICS economies is now reflected US$ 23 trillion, and its world share is expected to increase to 26 percent. Future growth in BRICS economies is expected to stabilize by 2025, with India and China being the primary drivers of the multiregional growth. BRICS countries have made significant progress in integrating with the global economy. Analysis of trading patterns within BRICS countries reveals that levels of intra-BRICS trade are pretty diverse, mainly reflecting the comparative sizes of the economies. Over the last couple of years, intra-BRICS employment and regional trade have increased nearly three times, supported by increased intra-regional business among member countries. An analysis of the intra-BRICS trade reveals that China has played a significant role by accounting for nearly half of the intra-BRICS trade, followed by India, Brazil, Russia, and South Africa. India is cautious about BRICS expansion. India's role in the neighboring SAARC agreement is central to its foreign policy. At the same time, India dominates sub-regional cooperation to promote economic growth, social progress, cultural development, and security in South Asia regions. India can use the strength and power of BRICS expansion to develop a strategy for regional cooperation within SAARC, BIMSTEC, and ASEAN member countries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".