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Chartbook 464 The"China squeeze" - the politics of development counterfactuals.
There are three types of China shock discourse. Each has a distinct temporal register. China shock 1.0 was a phrase coined by US academics in the 2010s to retrospectively summarize the impact on particular US labour markets, which they identified through painstaking empirical investigation. China shock 2.0 on everyone’s lips in Europe in the mid 2020s is an alarm raised by trans-Atlantic policy thinkers warning of a coming disaster which they project onto Europe’s ailing car industry. The third type of China shock discourse - commonly known as the “China squeeze” launched most recently by Indian economists Shoumitro Chatterjee and Arvind Subramanian in the pages of Foreign Affairs - mobilizes a different, more speculative temporal register: the counterfactual realm of alternate history. The China squeeze argument asks not what has happened, or what is going to happen, but what might have been. Specifically, what options for economic development might have been open to Global South economies like India or the economies of sub-Saharan Africa, had it not been for China’s spectacular industrialization since the late 1990s and the persistent competitiveness of China’s manufacture in low-skilled segments. Chatterjee and Subramanian’s argument is that whilst China has built a powerful position in electrical machinery and other high-skill manufacturing, which is now delivering China Shock 2.0, it also continues to run a trade surplus in low-skill, labour-intensive manufacturing. This surplus is large and has remained largely unchanged in fifteen years. Indeed, in the 2010s, in trade with low-income countries, China’s surplus rapidly increased. On their reading, this squeezes low-income producers in low-skill sectors in which they “should” be able to compete. Source: “China’s Mercantilist Squeeze on Developing Countries” Shoumitro Chatterjee and Arvind Subramanian. Peterson Institute for International Economics 26-7 May 2026 Chatterjee and Subramanian’s wording is telling: (emphasis mine) The canonical trajectory of economic development in the post-World War II period is for countries to transition from agriculture to manufacturing, first in low-skilled manufacturing and then later on to high-skill manufacturing (Herrendorf, Rogerson, and Valentinyi 2013). At the global level, this implies that high-income countries (HICs) that once specialized in low-skilled activities cede manufacturing export space to poorer countries that come along to occupy that space. In 1965, advanced economies accounted for about 60 percent of global value-added exports in four key low-skilled manufacturing sectors, i.e., apparel, leather, textiles, and footwear. Over time this share declined and began to be occupied first by the East Asian tigers and, beginning in the late 1990s, by China. Today China accounts for about 50 percent of the global market. The question is whether China, with its rising prosperity, is continuing to behave like its richer counterparts and ceding export space to poorer followers or to behave unlike them and continuing to occupy space. In terms of the conceptual maneuvers it performs, of the three China shock discourses, the “China squeeze” argument is by far the most ambitious. After all, it bases its critique of China on a counterfactual imagining of the world. Like any counterfactual argument, to construct this alternative reality it must rely on a heuristic model. To make their argument Chatterjee and Subramanian mobilize two key claims. The first reference point is the actual history of rich-country industrialization, what they refer to as the “canonical path”. The idea is that countries transition from agriculture to light industry and low-skilled manufacturing and from there up the value chain. To make this useful as a standard of comparison and a means to construct a normative standard, they adjust sectoral export shares for two factors: 1. the underlying level of economic development of the exporting country, as measured by national income and 2. the degree to which the sector in question is internationalized. The idea being that for a high income country to have a high export share in low-skill sectors is anomalous and even more so if that particular product is highly internationalized and thus suitable for being “conceded” to lower-income competitors. Where should this process end? Here Chatterjee and Subramanian introduce their second benchmark. Their normative idea of a global development path is one in which, in due course, low-skill manufacturing exports are distributed in proportion to a country’s share in the global labour force. They imagine, in other words, a world of proportional, polycentric global development without much national specialization in low-skill manufacturing. A useful benchmark is that, in labor-intensive manufacturing sectors, a country’s share of world exports should be broadly commensurate with its share of the world’s low-skilled labor endowment. … In the Heckscher-Ohlin model, this would be true if value added per worker and export propensities, i.e., fraction of output that is exported, are the same across countries. It is this pleasant liberal vista of orderly global development, progressing towards a general distribution of low-skilled manufacturing against which they judge reality and conclude that the low-income countries are suffering a “China squeeze”. China is not exiting low-skill sectors fast enough Allowing for its gdp level and the degree of globalization, China’s share of low-skill manufacturing exports is far higher than it “should” be. Relative to population, its low-skill share of exports is far too high. That in turn yields the conclusion that huge numbers of jobs - the authors suggest tens of millions - are being hoarded by China. For the four sectors captured in figure 4, this excess in value-added exports is $110 billion in 2022. For all low-skilled sectors overall captured in appendix figure D.1, excess value-added exports amount to $365 billion. The crowding out of LMIC exports by China is therefore substantial. Both these claims have in common that they are strong structuralisms. The first is that development paths ought to resemble each other. The second is that broadly speaking as far as low-skilled manufacturing is concerned, all countries are alike. If the world currently diverges from the distribution of trade implied by these assumptions, if China is not following the advanced economy path and has huge exports, this must be the result of “policy”, which the authors then put in question as illegitimate or unfair. Thus the naturalistic construction of a canonical path leading to a “level” distribution of low-skilled manufacturing reveals itself to be a polemical tool. From the point of view of China shock polemics, this discourse is no doubt welcome. But as an account of economic history, it must surely be regarded as nothing short of bamboozling. Development paths do not follow a regular, natural sequence. As David Fishman put it aptly, “development is not a queue”. They are always and everywhere, through and through political. Development is not so much a process, as a project. Each such project is more or less well adjusted to its context. As Gerschenkron taught uneven and combined development implies differentiation rather than simple imitation on a single parth. It may be true that Europe and the US exited relatively early from low-skill work. But clearly technology has changed. As C&S themselves point out, China no longer enjoys a low wage environment. Do they really believe that such huge differences can be accounted for either by industrial policy, which as they admit does not operate powerfully in low-skill sectors, or by exchange rate manipulation? What is overwhelmingly dominant in explaining the persistence of “low-skill” manufacturing in China are surely the network effects of complex supply chains. Indeed the label of “low-skill” may miss the point. The degree of globalization which Chatterjee and Subramanian decide to conjure away in their model of the development path - to allow for the fact that Europe and American textiles exporters did not enjoy just-in-time logistics in the 1950s - obscures the point that the networks through which Chinese factories supply the world are themselves key parts of the low-skill industrialization project. China isn’t knocking out 1970s style “cheap”. It has redefined the entire product cycle. C&S’s casual reference to “T-shirts” is telling. In today’s “fast fashion”, there is weight on both terms. Fashion and fast. China’s success in delivering on both at unprecedentedly high speed and at unprecedentedly low cost, isn’t a low-skill operation at all. If we see development trajectories not as the serial repetition of the same, but as distinctive, crafted projects that cumulate in complex agglomerations of skill, technology and labor, then this explains why the assumption that low-skilled manufacturing should follow the distribution of population flies in the face of all experience. As countless cases attest, low-wage, low-income developed economies are not by themselves the makings of a competitive production base. As Leon Liao puts it quite fairly: “International trade has never been allocated according to population. A country’s population gives it no natural claim to an equivalent share of global exports." And the remarkable fact is that Subramanian alone and with co-authors has long been making this point, not to pillory China, as is the case of the tendentious _Foreign Affair_s and Peterson pieces, but to highlight the great counterpart to China’s industrial success, namely India’s relative failure. The much-quoted Foreign Affairs piece showed low-skill export shares only for China, not for India. If you put both countries in the picture as Chaterjee and Subramanian have done on other occasions, the picture looks like this. China is far above the line, but India, almost as large in terms of population, is no less anomalous, just in the opposite direction. As far as global populations are concerned, and the imagining of tens of millions of “squeezed” jobs, it is this Sino-Indian pair that account for a huge share of the action. What this graph reveals is not China’s cheating, but India’s “greatest development failure”, at least this is the argument made Arvind Subramanian, this time in co-authorship with Devesh Kapur, in their major book, A Sixth of Humanity. Independent India’s Development Odyssey which appeared with Oxford University Press earlier this year. In this highly critical work on India’s development, China is repeatedly evoked, not to criticize but as a benchmark against which to illuminate what India’s political economy has not delivered i.e. large-scale formal employment for hundreds of millions of citizens. Kapur and Subramanian leave no doubt, if you want to understand why China, not India was the main driver of manufacturing globalization from the 1980s, don’t look to slots opening up in the division of labour thanks to the liberal mindedness of advanced economies, look to the contrasting political economy of the Maoist PRC and India’s post-independence political economy. As Kapur and Subramian note: The great divergence between China and India did not begin in 1978 with the Deng reforms—it was well underway by then. In one of the great ironies of modern history, the conditions created by Maoism turned out to be a great launching pad for industrial globalization. As the comparison of India and China in 1980 makes clear, to imagine manufacturing would be equally distributed when populations are so differently endowed in terms of educational and nutritional is fanciful. Here is the data from Kapur and Subramanian, data which I explored back at the very beginning of Chartbook. As Kapur and Subramanian insist, the striking fact is that even as India’s growth accelerated from the 1980s, structural change has not. Formal employment in India lags woefully behind. Why? As Kapur and Subramanian note, the path-dependent impact of India’s poor early start was devastating. The list of factors they mention is long and weighty: We argue for a new five-fold explanation applicable at different stages of Indian history: in the initial stages, the legacy of two key pre-1980s policies, the neglect of agriculture and the strangling of the domestic private sector, were critical. The failure of broad-based agricultural growth militated against rural industrialization, which would have been devoted to satisfying local needs that would have necessarily been labour intensive. Then, when the boom came after 1980, the thicket of regulation and broader labour protections that were legislated prematurely in a nascent democracy, underpinned by a deep ideological aversion to private capital in general and big capital specifically, became a barrier to attaining the size that would be necessary to compete globally. Similarly, the reforms after 1991, while wide-ranging, did not quite encompass non-tradeable inputs critical to manufacturing, namely, land, logistics infrastructure and power. A combination of low investment (logistics infrastructure), regulation (land) and the continued monopoly supply by state governments (power), combined with residual socialism, kept costs at 75–100 per cent above efficient supply. These factors were compounded on the supply side by the government, which dominated the formal labour market and established exorbitantly high wages at the lower end of the skill spectrum. This made their employment in the labour-intensive sector by the private sector less attractive. Finally, when the services sector and its exports boomed, wages soared even further via a Dutch Disease effect: one successful tradeable sector killed and cannibalized another less-skilled tradable sector, namely, manufacturing. Thus, scarcity-inducing policies of the planning era, precocious democracy and a Gandhian aversion to size; inefficient, monopolistic supply of critical non-tradable inputs; the behemoth of government; and super-successful skill-intensive services successively undermined India’s unskilled labour employment opportunities. The employment failure seems to have been over-determined. … Less quantifiable but no less important are some of the sociological factors that have undermined manufacturing and factory jobs. Take the impact of the success of the IT sector—located in urban areas with better working conditions, such as air-conditioned offices, good schools for children and attractive entertainment options. It became a more attractive place for engineering and management graduates to flock to. … Consider manufacturing and female employment. Indian society makes it difficult for women to work, reflected in India’s unusually low female labour force participation (elaborated in Chapter XIII). Indian society, in particular the routine harassment of women in public spaces, makes it even more difficult for them to travel long distances to take up work.37 Combined with onerous regulations on creating hostels and dormitories for women—which, in turn, prevents multiple shifts of operation—factories need to be located in areas with a large female labour pool. While firms can take apparel plants to female labour or bring them to the plants by building large-scale dormitories, this raises costs. If there was a case for subsidies to encourage labour-intensive manufacturing, housing subsidies to build dormitories for women workers would be a good place to start. All of this meant, that when opportunities did open up, in part thanks to adjustments in China, India was in no position to take advantage. Here is the account of the 2020s from Kapur and Subramanian. It stands in dizzying contrast to the one-sided, “China squeeze” argument delivered in the Peterson and Foreign Affairs pieces: In 2022, for example, India’s share of global exports in clothing (the canonical labour-intensive sector) was 3.1 per cent compared to 32 per cent for China. This is extremely disappointing because China started vacating export space in this sector after the Global Financial Crisis as its wages started rising; it then vacated further space in the aftermath of geopolitical developments that led investors to seek alternative investment locations. Between its peak and today, China lost about 7.5 percentage points of global export share (worth about $43 billion in 2022); over this period, India’s export share remained stagnant at 3 per cent, while that of Vietnam and Bangladesh rose by 3.5 to 4 percentage points. China’s loss did not translate into any gain for India in terms of low-skill exports and employment. Put differently, when the conditions for dynamism and prosperity were established after 1991, and even more tantalizingly when the global export opportunities opened up, it was as if India was a high-wage economy and only skilled labour could benefit from the dynamism. It had converted its physically abundant unskilled workforce into an economically expensive resource, penalizing its use. It is not my mission here to argue for or against Kapur and Subramanian’s interpretation of India’s development trajectory. The point in this context is simply that the “China squeeze” such as it is can only be understood, in relation to the heavy burden of domestic constraints that Kapur and Subramanian so unsparingly enumerate. I am concentrating here on India because it is the great counterpart to China and the unspoken reference point of the “China squeeze” discourse. But the point is more general. Can anyone with a straight face suggest that the main problems afflicting the development of South Africa or Nigeria, the great centers of mass underemployment in sub-saharan Africa, are cheap competition from China driven by Beijing’s industrial policy and an undervalued RMB? Likewise, is the main problem of the American working-class the threat of Chinese competition or the manifest crisis of social reproduction in the United States itself? The point here, as in the discourse around China shock 2.0 in Europe, is to insist that we should not normalize the world and pathologize China, without actually investigating what is going on in America’s industrial wastelands, the German car industry, or India’s lopsided labour market. One-sided pathologization should be understood for what it is, a polemical gesture. Concepts like China shock and China squeeze are, what Reinhart Koselleck, following Carl Schmitt, would have described as “asymmetrische Kampfbegriffe”, or “asymmetrical counter-concepts” or “asymmetrical combat concepts”. If the function of arguments like the “China squeeze” is to alert elites in the rest of the world of the need to rejuvenate and energize their development projects, so be it. But let us see the resulting discourses as the mobilizing interventions that they are. Interestingly, a significant slice of China’s public sphere - the so-called industrial party - have been obsessed for the last twenty years with precisely these questions of counterfactual economic history. Since the mid 2000s, a massive online discourse developed around an alternative history in which Chinese techno-patriots were asked to imagine how they would proceed if they had the possibility of traveling back in time to transport modern technology into the Ming dynasty (1368-1644) thus averting the “great divergence” of the 18th and 19th centuries. It is a fantasy of course, but also a goad. The point was not directed at Westerners. The alternate history is dramatically nationalist, but few n the West had even heard of it until recently. The adherents of the industrial party are not liberal moralists. They don’t project natural ladders of international development and ask why others don’t cede space. They take the Realpolitik of global economic development for granted. Their pointe was directed against fellow Chinese. The rallying cry of the alternative narrative was this: Now that we are beginning to gain steam and push forward on our national development path, now that we are breaking out of the inferior position assigned to us even in the early years following WTO accession, do not lose yourself in humanistic imaginings about better futures. In the spirit of Deng, they called on China to embrace the hard truth of development. Perhaps one might of the Industrial Party as a cultural trend born out of desire for symbolic revenge against those who had inflicted the century of humiliation. In terms of the various temporalities of the “China shock” - retrospective, prospective and counterfactual - one might think of the Industrial Policy discourse as truly speculative, conjuring up the China shock that never was. Or perhaps one might better think of it as imagining a world in which a powerful China was no shock at all, but simply a defining fact of modern history. I love putting out Chartbook. I am particularly pleased that it goes out for free to thousands of subscribers around the world. But, writing this newsletter takes a lot of work. If you are enjoying it and would like to support the project, sign up for one of the subscription options here. It is the equivalent of a fancy cup of coffee per month! Subscribe
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The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
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The “Science of Reading” Ignores the Science
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Multiple Hyde Park, Mount Lookout businesses closed amid flooding cleanup from heavy rain
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USNH Yokosuka Public Health Team Safeguards Community Water Supply
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Asian shares mostly decline with South Korea’s Kospi down 6.6%, while oil prices slip
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NBAA Heads to AirVenture to Highlight Business Aviation, Association Benefits
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Oil price jumps over 4% and gold slides as the US and Iran trade attacks –business live
Asian shares tumble with South Korea’s Kospi down nearly 10%
Hungary moves to overhaul university models banned from Horizon Europe
Hungary’s new government is aiming to overhaul the governance model of the institutions and universities that lost access to Horizon Europe and Erasmus+ funds “in a short timeframe,” according to Péter Horváth, the new state secretary for science policy and innovation. “As of today, the two non-university foundation-controlled institutions under my remit have been transformed,” he told Science|Business. “We hope the universities will follow and that this will be enough to satisfy the EU’s demands.”Under the previous government, led by Viktor Orbán and his Fidesz party, many academic and scientific institutions were restructured and made into special public trust foundations, with members strongly linked to the government given lifelong mandates and significant decision-making powers with little oversight. The European Commission deemed that this undermined academic freedom and transparency in the country, leading to a ban on 34 institutions in 2022, including 21 universities, which saw academics in Hungary lose access to Horizon Europe grants. The new Hungarian government, elected in May and led by Péter Magyar and his Tisza Party, has promised to dismantle this governance model and restore the institutions to EU programmes. As a result, the European Commission has promised to return access to the Erasmus+ education mobility programme, but so far no concrete agreement has been made on the Horizon Europe programme for research and innovation. Hungary has already made legislative changes in June to allow the institutions to be reformed and set a timeline for the implementation.The non-university foundations, which are mainly cultural centres such as the Foundation for Hungarian Culture or the Makovecz Campus Foundation, will all be dissolved by August 31 this year, a date tied to EU-set milestones that Hungary must meet to unlock frozen funds, with control transferred to relevant ministries. Meanwhile, the universities will have until 31 August 2027. For each university foundation, the government will set the dissolution date and the body to take over operations. There is no final decision on a permanent new model for the universities, according to Hungarian MEP Eszter Lakos, who is shadow rapporteur for the Horizon Europe specific programme, a separate piece of legislation detailing implementation rules for the EU’s next research programme, due to start in 2028. “The aim of the transition year is to settle this with [the universities], not to impose a model, and not to put them under state control,” she told Science|Business. “The goal is to give academic independence back to universities.”There are three models that are most likely to be implemented. One would be a return to a traditional, state-run model. Another could be a newer, more self-standing public institution. A third option would be a reformed version of the foundation models that meet EU standards. According to Lakos, the dismantling of the system put in place by the Orbán government is well underway and if all goes according to plan, Hungary could regain access to EU research money by the start of the next academic year in 2027. “I believe that the Hungarian government is doing the necessary changes so the universities could return as beneficiaries to Horizon from the next school year,” she said. In the meantime, “the universities, institutes and cultural assets carry on under proper public stewardship rather than a handful of unaccountable trustees,” said Lakos. The laws passed in June impose new safeguards: board terms are capped at four years and renewable only once, appointments are made through open competitions and sitting politicians cannot join joining these boards.It remains unclear whether a domestic science funding programme set up as a back-up scheme by the former government following the EU funding ban, called HU-rizon, could be continued. “This programme should never have had to have been established in the first place, but it has proven to be quite popular,” he said. “I am considering continuing this programme with a refined focus on helping international collaborations.”Re-organising the research network One of the first priorities for Horváth and his cabinet is to resolve questions over the future of the Hungarian Research Network, Hun-Ren. The network of academic institutes was taken away from the Hungarian Academy of Sciences in 2019 and turned into a quasi-private organisation, with similarities in its governance to the public trust foundations.Horváth and his team have consulted over 5,000 representatives from the network and the conclusion is broad unhappiness with the directors of all the institutes involved. “We have presented the results to the president and the chief executive of the network and this is currently being discussed,” Horváth said. The plan is to re-integrate the network back into the Academy of Sciences but in an improved way, “learning from mistakes of the past,” he added. The government also wants to reintegrate four humanities and social science research centres into the network that the previous government had transferred to Eötvös Loránd University. The transfer brought sharp criticism from the academic community, with a group of Hungarian research heads, including European Research Council grant recipients, sending an open letter to Orbán warning that the transfer would “cause historically significant harm to the entirety of Hungarian scientific life.” The transfer was “one of the biggest shames in Hungarian research in the past 20 years,” Horváth said. “We want to immediately re-integrate them back into the research network and to regain the trust of these institutions, because the way they were treated was really unfair.”Another pressing issue is the Élvonal Excellence Research and Talent Development Foundation, led by Nobel laureate Ferenc Krausz. The foundation signed a financing agreement with the former government earlier this year for a budget of over €730 million over the next five years. The goal is to create a world-class centre to attract top talent from abroad and to develop local researchers. But there was little transparency about this foundation, and news of its huge budget, which is nearly as much as Hungary’s entire research budget, caused a stir in the media following the recent elections. Another issue is that, as with the foundation boards of the institutes banned from Horizon Europe, there was little-to-no oversight of decisions led by Krausz. “It was an excellent idea but an unacceptable execution,” Horváth said of the foundation. “The fact that this is out of the Hungarian funding scheme, mostly concentrating on one person who decides on the budget is unacceptable for us.”The government plans to merge the centre with the National Research, Development and Innovation Office, the country’s R&D funding agency, with a reduced budget. Horváth is hopeful that Krausz will still be involved. The new government’s R&D goalsA phrase that crops up regularly during the discussion with Horváth is “democratic process.” The new state secretary is determined to involve Hungary’s research community in shaping future policies. This marks a departure from the previous government’s approach, and several people in Hungary’s research community have commented on the openness of the new government. In terms of concrete goals, Horváth and his team already have plans. He wants to create a new science fund in Hungary, based on the best practices of other European countries. The fund would not be tied to annual government budgets and would provide long-term, stable financing. “If we were to succeed in creating this fund, then I think it would be one of the biggest achievements for me in this period of government,” Horváth said. On the innovation side, he is looking into how best to bring in the private sector. “We want to make sure that we are working with the private sector to support innovation,” Horváth said. One of his big aims is to introduce entrepreneurship teaching into high schools. Hungary already has a reputable national academy offering research and innovation training in the field of natural sciences, and Horváth wants to expand this to all disciplines and across the whole country. “One of the main ways to elevate our innovative businesses is to teach our children to be innovative,” he said. “This will probably need ten years to pay off, but this is what we should do. Our aim is to make Hungary strong in our region, and this is what is needed.” Related articlesHungary’s Horizon Europe performance in numbersCommission unlocks Erasmus+ cash for Hungary, Horizon could be next‘Academic Huxit.’ Hungarian researchers speak out on impact of EU ban A more difficult task will be funding. The new government is aiming to increase research spending to 2% of the GDP by 2030, and then increase it to 3% in line with EU objectives. Currently, spending sits around 1.3%. But according to Horváth, the current budget, inherited from the previous government, is “heavily in the negative,” so any plans to increase research spending will have to start next year. Achieving 2% by 2030 already needs a big push, almost doubling the research budget. “This is something we’d definitely like to reach, and something I can see us achieving,” he said. “From the 2030s, I’d like to see an innovative generation growing up that can help us reach the 3% target.” Positivity in the new governmentDespite the many challenges facing Horváth and his team, the mood is positive. “It feels a bit like a start-up right now. Everyone is working 24/7, day and night, trying to do as much as they can. There is a lot of energy,” he said. It is a big change for the state secretary who, like many in his cabinet, is coming from a background in research or business, and not in politics. “Six weeks ago, I was sitting with my microscope and my research PhDs, so it’s been a big change for me,” said the computer scientist, who was previously the director of the Institute of Biochemistry at the Hun-Ren Biological Research Centre in Hungary and worked at the Institute for AI for Health at Helmholtz Munich. But he is relishing the task to transform the country’s R&D landscape. “We feel enormous support from the Hungarian people, but also from Europe,” he said. “We’ve received a lot of letters of support from around Europe. There is big trust there, and huge responsibility on our side. We want to get everything back on track, and there’s a lot to do.”
In Photo: Girls basketball sports camp - UW-Oshkosh Today
The University of Wisconsin–Oshkosh plays host to a number of sports camps taking place throughout the summer. A girls basketball camp June 30-July 2 featured around 100 young players under the leadership of new UWO assistant coach Claire Levendoski with help from student-athletes. Check out photos below: Learn more: UW-Oshkosh Titans
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Katie Couric (@katiecouric)
3,068 likes, 268 comments - katiecouric on June 17, 2026: "Rahm Emanuel has been a major force in Democratic politics for decades—from congressman and White House chief of staff to mayor of Chicago and U.S. ambassador to Japan. As the 2026 midterms approach, he joined me on Next Question to discuss President Trump's second term, why Democrats "lost the plot," why he believes the U.S. should end taxpayer-funded military aid to Israel, and what it will take for the party to reconnect with voters and regain lost ground. 🎧 Watch the full interview on YouTube or listen wherever you get your podcasts.".
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‘Almost dying wasn’t on my bingo card’: Simone Biles suffers health scare
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Overnight Science Saturday News Digest May 30th, 2026
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Oshkosh dad starts ‘Politics in the Park’ for civil conversations
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Oshkosh dad starts 'Politics in the Park' for civil conversations
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Will Brian Flores Ever Get Another Head Coaching Job?
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Olympiakos beats Real Madrid 92-85 to win EuroLeague title
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Roundup: More identity verification tech for digital health exchanges
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Politics in the Park conversations in Oshkosh aim to build community
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10 Gems of Bluesky Today
Greetings everyone. I’m writing this from my phone, which is doable, but a little clunky. One problem is that I can’t see image attributions from the image library, so I apologise in advance that I…
Rousey vs. Carano results: Robelis Despaigne brutally KOs Junior dos Santos in first-ever MMA fight on Netflix
These grandparents sit on benches, ready to talk to strangers who need them
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by Miranda Dunlap / Wisconsin Watch, Wisconsin Watch May 13, 2026 Click here to read highlights from the story Oshkosh resident Nikolas DeGroot started
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Nikolas DeGroot started informal in-person gatherings about shared issues in local parks and makes sure conversations stay respectful.
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Sega’s Yakuza prequel stars an actor who’s been dead for more than a decade
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West Texas small business owners recognized during annual luncheon
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When NVIDIA first revealed DLSS 5 and its neural rendering, a lot of the online backlash that was leveled at the feature centered around Capcom's Resident Evil character, Grace, and how DLSS 5 changed her facial features. Now, in a recent interview with Eurogamer, Koshi Nakanishi and Masato Kumzawa,...
2.3K views · 28 reactions | Spirit Airlines has announced it's going...
Spirit Airlines has announced it's going out of business after 34 years. The low-cost US carrier says all its flights have been cancelled as it begins an "orderly wind-down of operations." It cited...
Free, discounted movies return to San Antonio theaters this summer
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