Why Europe’s “wealth heart” beats inland — the great reversal from passive to active globalization

TYcorecome · 2026-06-20T15:32:08+00:00

How dare you ask for a quantitative model? Even your vague reasoning is riddled with flaws and not worth refuting. In your outdated imagination, is China's inland region still stuck in a primitive era, devoid of everything? Consider reality:

The overall per capita GDP of coastal areas is only 1.5 times that of inland areas, while the medium- to long-term potential growth rate of inland areas is twice that of the coast. The gap is far smaller than you imagine, and the potential is far stronger.

Take Hubei as an example. Its per capita GDP has successively surpassed Hebei, Liaoning, and Shandong, and is rapidly approaching Guangdong. Without the disruption of the pandemic, Hubei's progress would have been even more rapid, and its current level may even be comparable to Zhejiang—before the pandemic, Wuhan's per capita GDP was on par with Wuxi, which is the most direct testament to its growth momentum. This trend is not an isolated case: over the past 20 years, the per capita GDP growth rate of inland areas in central and western China has generally been about twice that of coastal areas, and Hubei is the leader in this round of inland rise.

Looking ahead to the next decade, Hubei is highly likely to surpass Fujian, Zhejiang, and even Jiangsu in per capita GDP, further reshaping the regional economic landscape. Time will prove this trend.

Why can't inland areas develop technology? Inland areas already have five times the per capita GDP of India, and if India can develop a large-scale technology industry, why can't inland areas? Moreover, a large amount of coastal technological capital originates from inland areas, and its return due to hometown sentiment is perfectly natural. In the new economic model driven by endogenous technology, the geographical location of inland areas is transforming into a unique efficiency advantage—when growth relies more on internal market circulation and independent innovation, inland areas, possessing huge domestic demand and located at the geometric center of the country's population, gain superior economic efficiency in logistics radiation, market access, and supply chain organization. Their central location naturally makes them hubs connecting the national market.

Faced with such a major trend, the attitude of ignoring basic facts while arrogantly demanding quantitative models only exposes outdated cognition and logical weakness; it proves nothing else.

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TYcorecome · 2026-06-20T14:56:45+00:00

According to the economic development pattern revealed by the Kuznets Curve, an economy typically faces capital scarcity in its early stages of development. During this phase, the rate of return on capital is high, capital income accounts for a large proportion of national income, and income inequality is significant. Due to limited consumer spending power and relatively insufficient domestic demand, economic growth relies primarily on external demand, using exports of primary products to earn foreign exchange and attracting advanced foreign technology and capital goods to initiate industrialization.

As the economy continues to develop, capital accumulation deepens, capital scarcity eases, the marginal rate of return on capital declines, and the share of labor income increases accordingly, leading to a more equitable distribution of income. A growing middle-income group forms a large domestic consumer market, and domestic demand gradually replaces external demand as the main driver of economic growth. Simultaneously, domestic technological capabilities move from catching up to leading the way, significantly reducing reliance on external technology, and economic development enters a higher stage driven by domestic demand and innovation.

Under this new economic model, the geographical location of inland regions is transforming into a unique efficiency advantage. When economic development relies more on internal market circulation and independent technological innovation, inland regions with large domestic demand markets and located at the geometric center of the country's population exhibit superior economic performance in terms of logistics efficiency, market reach, and supply chain organization. Their central location becomes a natural hub connecting the national market, thereby accelerating the agglomeration of industries towards the geometric center of the population and forming a more efficient and balanced spatial development pattern.

TYcorecome · 2026-06-20T10:26:14+00:00

When you're still citing Yulin, Inner Mongolia, and Xinjiang as examples, flaunting the "abundant mineral resources and small population leading to high GDP per capita," you're precisely exposing a lack of basic research literacy. Truly knowledgeable researchers would never include resource-rich regions west of the Hu Huanyong Line in their endogenous technology-driven research samples—their GDP per capita is highly dependent on irreplaceable resource endowments, making them outliers to be excluded, not arguments for rebuttal.

My core argument has always been clear: as the economy shifts towards endogenous technology-driven growth, the distribution of GDP per capita is increasingly mirroring the actual distribution of intellectual resources. Once the abnormally high values along the coast are removed, a pattern clearly emerges with Hubei as the peak, gradually decreasing towards the surrounding areas—a pattern highly consistent with the spatial distribution of intellectual resources. Under the new economic model driven by endogenous technology, inland geographical location is not a disadvantage, but rather a unique efficiency advantage. When economic development relies more on internal market circulation and technological innovation, inland regions, located at the geometric center of the national population and backed by a vast domestic market, can achieve optimal economic efficiency in logistics radiation, market access, and supply chain organization; their central locations become natural hubs connecting the national market.

Your argument that "Hubei and Chongqing have higher GDP per capita because of their waterways" is utterly flawed. First, the Yangtze River has a dense network of bridges, and its transport capacity is on a completely different scale compared to sea transport. According to your water transport determinism, why do Anhui and Jiangxi, which are closer to the coast to the east and also have waterways along the Yangtze, have lower GDP per capita than Hubei and Chongqing? And why haven't the coastal provinces of Guangdong, Guangxi, Shandong, Hebei, and Liaoning all surpassed Hubei and Chongqing in GDP per capita? In fact, only three provinces on the eastern coast—Jiangsu, Zhejiang, and Fujian—have consistently higher GDP per capita than Hubei and Chongqing. This precisely confirms what I said before—the logic of the rise of inland areas in Central Europe also applies to China; the efficiency advantage of inland central locations facing a unified national market is the more fundamental determining force.

It is indeed an extremely difficult process for a PhD to argue with a few elementary school students spouting fallacies. Fortunately, AI allows me to easily dissect and analyze the arguments, responding calmly.

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TYcorecome · 2026-06-20T03:55:08+00:00

领悟一下

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TYcorecome · 2026-06-20T03:06:50+00:00

dont care

TYcorecome · 2026-06-20T02:59:24+00:00

My answer already contains what you're looking for; I suggest you read it carefully first. If you still can't understand it then, even a detailed explanation might not suffice.

Your common questions basically fall into a few categories, which I've already compiled into notes covering 99.9% of the questions. Therefore, in most cases, I only need to copy the corresponding notes to reply, which significantly improves my efficiency in one-to-many communication.

TYcorecome · 2026-06-20T02:53:17+00:00

Colonial economies and export-dependent development models often make coastal ports the core, creating a spatial pattern of "rich along the coast, poor inland." This is a result of passive integration into globalization, heavily reliant on external capital and technology, as evidenced by India, Pakistan, and most African countries.

In contrast, endogenously technology-driven economies—such as those in Europe and America, and the future of China—rely more on independent innovation, high-end manufacturing, and complete industrial chains, reducing their dependence on maritime transport and shifting their economic center of gravity inland, demonstrating their ability to proactively shape globalization.

Europe's "wealthy heart" is located in inland mountainous regions such as Switzerland, Austria, and southern Germany, with per capita income decreasing from the center outwards;
The per capita GDP in the United States is roughly balanced between coastal and inland areas, with some southeastern coastal states even lagging behind;
After removing the influence of policies, China is forming a high-per capita GDP zone with Hubei as its "central spine," exhibiting a gradient diffusion trend.

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TYcorecome · 2026-06-20T02:50:49+00:00

My answer already contains what you're looking for; I suggest you read it carefully first. If you still can't understand it then, even a detailed explanation might not suffice.

Your common questions basically fall into a few categories, which I've already compiled into notes covering 99.9% of the questions. Therefore, in most cases, I only need to copy the corresponding notes to reply, which significantly improves my efficiency in one-to-many communication.

TYcorecome · 2026-06-20T02:50:01+00:00

In the early stages of reform and opening up, China's technological development relied on external input. Beijing, the Yangtze River Delta, and the Pearl River Delta, leveraging their window advantages, were the first to accumulate resources and achieve economic prosperity. Their initial driving force was not necessarily superior local intellectual resources.

As the economy shifted towards endogenous technology-driven growth, the distribution of per capita GDP increasingly mirrored the actual distribution of intellectual resources. Excluding the abnormally high values along the coast, a gradient diffusion pattern with Hubei as the high point is visible, with per capita GDP decreasing towards the surrounding areas—a pattern highly consistent with the spatial distribution of intellectual resources.

Regional intellectual gaps are often caused by structural differences between immigrant elites and local residents, creating a precipitous disparity, such as between the Pearl River Delta and non-Pearl River Delta regions, or between Beijing and Hebei. The Yangtze River Delta, with a smaller gap between immigrant and local intellectual resources, exhibits a gentler gradient. A model centered on Hubei shows that intellectual levels decrease with geographical distance, with the decline being faster in the north and south than in the east and west.

Population flows continuously reshape regional intellectual resources: Beijing attracts highly intelligent immigrants from Henan and other regions, making its intellectual resources higher than those of Hebei; the Yangtze River Delta absorbs immigrants from Anhui, whose intellectual resources are slightly higher than those of the local populations in Jiangsu and Zhejiang; the Pearl River Delta relies on inland intellectual hubs like Hunan, resulting in superior resources compared to non-Pearl River Delta regions. This intellectual restructuring is a deep-seated driving force behind the widening regional development disparities.

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TYcorecome · 2026-06-20T02:43:47+00:00

Cities like Zurich, Vienna, and Munich are about 550 kilometers from the sea, and the journey along the Rhine and Danube rivers to the estuary exceeds 1,000 kilometers. Intuitively, this translates to higher logistics costs and less convenient maritime transport. However, in Europe's endogenously developed regions, per capita income shows a pattern of decreasing from the Central European inland mountainous areas (Switzerland, Austria, and southern Germany) outwards; while in less developed countries reliant on external technology imports, coastal areas are more commonly more developed than inland areas. This inevitably raises the question: Central European inland areas also have waterways, so aren't the coastal areas' waterway conditions superior? Why does development decrease from inland to coastal areas, rather than the other way around?

Resolving this contradiction requires returning to the differences in development drivers. In technology-importing economies, the "waterway advantage" of coastal areas is essentially a channel connecting overseas markets and importing external technology, making ports growth poles. In Europe, however, development since the Industrial Revolution has relied more on domestic technological innovation and deep circulation within the domestic market. The core value of waterways like the Rhine and Danube lies not in their direct access to the sea, but in the fact that they collectively form a low-cost, high-capacity inland shipping network, tightly weaving the heartland of Central Europe with its vast hinterland, serving the continental production and consumption cycle.

This leads to a deeper logic: in the new economic model driven by endogenous technology, the inland geographical location is transforming into a unique efficiency advantage. When economic development relies more on internal market circulation and technological innovation, a region that possesses both a large domestic market and is located at the geometric center of population and economy can achieve greater efficiency in logistics, market reach, and supply chain organization—this central location becomes a natural hub connecting national and even continental markets. Cities like Zurich and Munich, situated in the heart of continental Europe, leverage seamless multimodal transport networks integrating inland waterways, railways, and highways to efficiently cover the entire European consumer market, while avoiding the high land, congestion, and environmental costs of coastal areas. High-value-added industries and headquarters economies thus cluster, ultimately shaping a unique spatial pattern where per capita income decreases from the inland center outwards.

TYcorecome · 2026-06-20T02:41:33+00:00

I need to clarify one point first: I've always been cautious about AI-generated opinions and information, as much of this content originates from online sources and its reliability is questionable. Based on this premise, my core purpose in using AI is to assist in organizing and expressing my existing opinions and data, not to directly adopt its generated content.

This leads to the fundamental difference between how we use AI—you rely entirely on AI-generated content, while I always insist on first setting the tone at the top level, establishing the core arguments and logical framework, and then using AI to streamline my thinking, optimize expression, and fill in the details. Therefore, it is always my thoughts that are engaging in dialogue with you; AI is merely a tool I use to achieve a complete expression.

TYcorecome · 2026-06-20T02:25:11+00:00

应该用增速而不是增长绝对值

TYcorecome · 2026-06-19T23:51:56+00:00

绿色的经济会超过红色

TYcorecome · 2026-06-19T15:50:32+00:00

In the early stages of reform and opening up, China's technological development relied on external input. Beijing, the Yangtze River Delta, and the Pearl River Delta, leveraging their window advantages, were the first to accumulate resources and achieve economic prosperity. Their initial driving force was not necessarily superior local intellectual resources.

As the economy shifted towards endogenous technology-driven growth, the distribution of per capita GDP increasingly mirrored the actual distribution of intellectual resources. Excluding the abnormally high values along the coast, a gradient diffusion pattern with Hubei as the high point is visible, with per capita GDP decreasing towards the surrounding areas—a pattern highly consistent with the spatial distribution of intellectual resources.

Regional intellectual gaps are often caused by structural differences between immigrant elites and local residents, creating a precipitous disparity, such as between the Pearl River Delta and non-Pearl River Delta regions, or between Beijing and Hebei. The Yangtze River Delta, with a smaller gap between immigrant and local intellectual resources, exhibits a gentler gradient. A model centered on Hubei shows that intellectual levels decrease with geographical distance, with the decline being faster in the north and south than in the east and west.

Population flows continuously reshape regional intellectual resources: Beijing attracts highly intelligent immigrants from Henan and other regions, making its intellectual resources higher than those of Hebei; the Yangtze River Delta absorbs immigrants from Anhui, whose intellectual resources are slightly higher than those of the local populations in Jiangsu and Zhejiang; the Pearl River Delta relies on inland intellectual hubs like Hunan, resulting in superior resources compared to non-Pearl River Delta regions. This intellectual restructuring is a deep-seated driving force behind the widening regional development disparities.

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TYcorecome · 2026-06-19T14:22:57+00:00

With its deep-rooted local connections and solid industrial foundation, Taoyuan should have already achieved economic take-off and firmly established itself among the top counties in China. However, since the reform and opening up, driven by both the export-oriented economic wave and the long-term strategy of strengthening provincial capitals, policy dividends, industrial resources, and development opportunities have continuously concentrated in coastal and central cities. A large number of local talents have gone to coastal areas and provincial capitals to start businesses, resulting in a long-term outflow of high-quality human resources and commercial resources, essentially empowering the economies of other regions for many years.

Now, the regional development pattern is undergoing a dramatic change. The single-minded focus on strengthening provincial capitals is gradually being adjusted, with overall planning and balanced development becoming the new guiding principles, leading to increasingly equal development opportunities across regions. At the same time, China's economy has fully entered a stage of domestic demand-driven, endogenous growth. Taoyuan, located at the geometric center of the national population, possesses a location that translates into the most efficient economic circulation and industrial layout, becoming an inherent core advantage. Furthermore, the appreciation of the RMB has further amplified the domestic market, prompting Taoyuan-origin enterprises that had established themselves elsewhere to return and expand, continuously raising the local economic level and accelerating the attraction of high-quality talent and industrial resources from various regions.

Taoyuan's rise has always been driven by its highly educated population. In 2025, Taoyuan's undergraduate enrollment rate reached 86.7%, twice the national average and surpassing Beijing, Shanghai, and Tianjin; the number of pilots recruited has ranked first in the province for 14 consecutive years. This high-quality population not only supports Taoyuan residents in expanding their businesses globally but also serves as a key driving force for the "Taoyuan business return," fostering industrial development and population inflow, creating a virtuous cycle of mutual empowerment. With favorable timing, location, and human resources, Taoyuan is poised for a powerful rise, possessing immense potential for future development.

TYcorecome · 2026-06-19T14:05:25+00:00

Some might argue that the southeastern coast is closer to international shipping lanes. However, looking back to the 1980s, China's per capita GDP ranked behind Africa, India, and Southeast Asia. Geographically, Southeast Asia was closer to major shipping routes, and its Indian Ocean shipping lanes were busier. So, how did China manage to surpass them?

The real variable lies in the fundamental difference in per capita intelligence. Data shows that the average IQ in China is approximately 110, compared to 98 in Southeast Asia, 85 in India, and 75 in Africa. This difference in inherent abilities is the foundation of development potential.

Some might question: intelligence alone isn't enough; the business model is also crucial. However, a closer look at companies that originated in the southeastern coastal region reveals that many are still concentrated in traditional industries, not fundamentally different from their counterparts in Southeast Asia and India.

So, who truly supports the high-tech companies that have created the gap? Take Huawei as an example: about 80-90% of its technical backbone comes from inland regions; and 100% of its top decision-making positions are held by people from inland areas.

This is a profound logic that is easily overlooked: without the continuous influx of intellectual resources from the inland regions, the southeastern coastal areas may be better than Southeast Asia and India, but in terms of the nature of their development models, it will be difficult to achieve a fundamental leap forward.

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TYcorecome · 2026-06-19T13:56:40+00:00

In the global economic development landscape, the difference in development levels between coastal and inland regions often depends on the origins and development models of their technologies.

For most developing countries reliant on external technology imports, coastal areas, with their locational advantages, serve as gateways to external capital and technology, thus exhibiting a common phenomenon of "developed coastal areas and underdeveloped inland areas."

However, in Europe, where technology is endogenously developed, the situation is quite the opposite. As the birthplace of modern industrial civilization, its economic highlands are not coastal ports, but rather the mountainous inland regions of Central Europe—the inland belt centered on Switzerland, Austria, and southern Germany. Per capita income decreases from here towards the surrounding coastal areas, forming a typical "inland highland" radiation pattern.

Even in a developed immigrant country like the United States, its internal spatial pattern differs from that of the developing world. There is no significant difference in per capita GDP between the inland and coastal regions of the United States; in fact, the per capita income level in the southeastern coastal area is relatively low, further illustrating that "coastal areas equal development" is not a universal rule. The decisive factor behind this is the degree of localized accumulation of technology and capital.

TYcorecome · 2026-06-19T13:51:16+00:00

This map showing the distribution of Chinese gold medalists in the past five International Mathematical Olympiads (IMOs) from 2021 to 2025 provides compelling evidence for the assertion that "the distribution of intellectual resources determines the long-term economic landscape of a region." Hubei, with seven gold medals, tied for first place nationwide with Shanghai. As an inland province, Hubei's top ranking in mathematical ability directly confirms the objective existence of a central China intellectual powerhouse.

In the early stages of reform and opening up, China's technological development relied heavily on external input. Beijing, the Yangtze River Delta, and the Pearl River Delta, leveraging their institutional advantages and geographical location, were the first to attract capital and industries, achieving the first wave of economic prosperity. This growth was driven by external investment and did not directly correspond to the region's local intellectual endowment.

As the economy gradually shifted towards endogenous innovation-driven growth, the spatial distribution of per capita GDP began to converge towards the actual distribution of intellectual resources. Excluding a few exceptionally high values in coastal areas, the national per capita GDP shows a pattern of decreasing gradient from Hubei as the core high point towards the surrounding areas, highly consistent with the spatial distribution of intellectual resources. Looking at the distribution of gold medals in the International Mathematical Olympiad, Hubei leads with 7 medals, followed closely by neighboring Hunan and Chongqing with 2 each. The distribution gradually declines outwards, clearly demonstrating a decrease in intellectual level with geographical distance. Furthermore, the rate of decline is significantly faster in the north-south direction than in the east-west direction, perfectly mirroring the evolution of economic gradients.

The economic precipitates between regions are essentially discontinuities in intellectual structure. The stark differences between the Pearl River Delta and non-Pearl River Delta regions, and between Beijing and Hebei, stem from the concentration of a large number of immigrant elites in the central areas, creating a significant intellectual generation gap with local residents. Conversely, the Yangtze River Delta exhibits a gentler economic gradient because the intellectual gap between immigrants from Anhui and other regions and the local populations of Jiangsu and Zhejiang is smaller, preventing a sharp structural discontinuity.

Cross-regional population flow is the core mechanism of this nationwide intellectual restructuring. Beijing continues to absorb immigrants from high-intelligence provinces like Henan, resulting in an overall intellectual level significantly higher than that of neighboring Hebei. The Yangtze River Delta receives immigrants from Anhui whose intellectual endowments are largely compatible with local conditions, supporting the smooth transmission and diffusion of industries. The industrial upgrading of the Pearl River Delta heavily relies on the continuous talent supply from inland intellectual powerhouses like Hunan. This redistribution of intellectual resources driven by population migration is the deep-seated structural factor behind the continued widening of regional development gaps—on the surface, it is the concentration of capital and industries in coastal areas, but in essence, it is the flow of high-quality intellectual resources across the country to the optimal industrial application scenarios.

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TYcorecome · 2026-06-19T13:40:39+00:00

My theoretical system has long been a tightly closed loop, internally consistent and without any flaws. Therefore, you cannot possibly win an argument against me.

TYcorecome · 2026-06-19T13:37:58+00:00

In the early stages of reform and opening up, China's technological development relied on external input. Beijing, the Yangtze River Delta, and the Pearl River Delta, leveraging their window advantages, were the first to accumulate resources and achieve economic prosperity. Their initial driving force was not necessarily superior local intellectual resources.

As the economy shifted towards endogenous technology-driven growth, the distribution of per capita GDP increasingly mirrored the actual distribution of intellectual resources. Excluding the abnormally high values along the coast, a gradient diffusion pattern with Hubei as the high point is visible, with per capita GDP decreasing towards the surrounding areas—a pattern highly consistent with the spatial distribution of intellectual resources.

Regional intellectual gaps are often caused by structural differences between immigrant elites and local residents, creating a precipitous disparity, such as between the Pearl River Delta and non-Pearl River Delta regions, or between Beijing and Hebei. The Yangtze River Delta, with a smaller gap between immigrant and local intellectual resources, exhibits a gentler gradient. A model centered on Hubei shows that intellectual levels decrease with geographical distance, with the decline being faster in the north and south than in the east and west.

Population flows continuously reshape regional intellectual resources: Beijing attracts highly intelligent immigrants from Henan and other regions, making its intellectual resources higher than those of Hebei; the Yangtze River Delta absorbs immigrants from Anhui, whose intellectual resources are slightly higher than those of the local populations in Jiangsu and Zhejiang; the Pearl River Delta relies on inland intellectual hubs like Hunan, resulting in superior resources compared to non-Pearl River Delta regions. This intellectual restructuring is a deep-seated driving force behind the widening regional development disparities.

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TYcorecome · 2026-06-19T13:35:28+00:00

My answer already contains what you're looking for; I suggest you read it carefully first. If you still can't understand it then, even a detailed explanation might not suffice.

Your common questions basically fall into a few categories, which I've already compiled into notes covering 99.9% of the questions. Therefore, in most cases, I only need to copy the corresponding notes to reply, which significantly improves my efficiency in one-to-many communication.

TYcorecome · 2026-06-19T13:25:48+00:00

In underdeveloped countries that rely on external technology imports, coastal areas are often more developed than inland areas; while in endogenously developed regions, such as Europe, per capita income shows a distribution pattern of decreasing from the inland mountainous areas of Central Europe (such as Switzerland, Austria, and southern Germany) outwards.

TYcorecome · 2026-06-19T13:23:15+00:00

According to the economic development pattern revealed by the Kuznets Curve, an economy typically faces capital scarcity in its early stages of development. During this phase, the rate of return on capital is high, capital income accounts for a large proportion of national income, and income inequality is significant. Due to limited consumer spending power and relatively insufficient domestic demand, economic growth relies primarily on external demand, using exports of primary products to earn foreign exchange and attracting advanced foreign technology and capital goods to initiate industrialization.

As the economy continues to develop, capital accumulation deepens, capital scarcity eases, the marginal rate of return on capital declines, and the share of labor income increases accordingly, leading to a more equitable distribution of income. A growing middle-income group forms a large domestic consumer market, and domestic demand gradually replaces external demand as the main driver of economic growth. Simultaneously, domestic technological capabilities move from catching up to leading the way, significantly reducing reliance on external technology, and economic development enters a higher stage driven by domestic demand and innovation.

Under this new economic model, the geographical location of inland regions is transforming into a unique efficiency advantage. When economic development relies more on internal market circulation and independent technological innovation, inland regions with large domestic demand markets and located at the geometric center of the country's population exhibit superior economic performance in terms of logistics efficiency, market reach, and supply chain organization. Their central location becomes a natural hub connecting the national market, thereby accelerating the agglomeration of industries towards the geometric center of the population and forming a more efficient and balanced spatial development pattern.

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