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HOMETOWN ENTERTAINMENT: Jim Messina to perform first Roanoke concert tonight at Jefferson Center
Jim Messina performs at the Jefferson Center Thursday at 7:30 p.m. for his first show in the city.
When papers become currency: a Chinese debate about trust in science
Last Saturday, 31 October, I went to the University of Hong Kong’s Beijing Centre for its Talent Forum. It was the fourth stop in the series this year, following events in Shanghai’s Zhangjiang, Shenzhen’s Qianhai, and on HKU’s main campus. The programme covered a remarkable distance in one afternoon. HKU’s Xiao-Jing Wang discussed computational neuroscience, intelligence, and the prefrontal cortex—before even delivering his inaugural public lecture to students back in Hong Kong. His colleague Bing Zhang took us from the Big Bang to artificial intelligence. Tsinghua’s Xue Lan asked how AI might reshape the institutional infrastructure underpinning higher education. There were lively panels featuring industry leaders from JD.com, Xiaomi, Haier—and Kaiser Y Kuo on the closing panel discussing innovation and international connections. I cannot pretend to have followed every detail of the brain models or the astrophysics. The talk that stayed with me was closer to something we have covered before: Zhou Zhonghe 周忠和 on papers, evaluation, and scientific trust. Zhou is a palaeontologist, an Academician of the Chinese Academy of Sciences, and an international member of the US National Academy of Sciences. He is also editor-in-chief of The Intellectual (知识分子), China’s leading science commentary platform. His subject was uncomfortable enough for a room full of successful academics: what happens when the system for recognising good science starts rewarding something else? Part of my interest came from our sister newsletter, The East is Read, which covered the controversy around “Geng Tongxue” in May. A PhD dropout from Beihang University, Geng has publicly challenged papers by prominent researchers through detailed online allegations of manipulated images and fabricated data. At Tongji University, an investigation into a challenged Nature paper found academic misconduct, and the dean of its life sciences school was removed. The affair brought doubts about academic integrity well beyond laboratories and university committees. How could someone outside the established hierarchy spot problems in papers that had passed through prestigious journals and institutions? And what, exactly, had all that prestige guaranteed? Zhou approached these questions through two essays published in July by The Intellectual: one by Wang Xiaodong, director of the National Institute of Biological Sciences, Beijing, and a response by Wang Liming, of Shanghai’s Shangsi Institute of Natural Sciences. Both began with the controversy over Geng. Their arguments deserve a wider audience, so I want to put parts of them alongside what Zhou said on Saturday. Wang Xiaodong’s starting point is evolution. A research system selects for the behaviour it rewards. Grants, jobs, journals, talent programmes, and prizes collectively determine which scientists prosper and which practices get passed down from advisors to students. “Whatever the system rewards is what it will evolve to produce,” he writes, citing the ancient Chinese saying: The King of Chu loved slender waists, and many in the palace starved to death. That is a more demanding diagnosis than saying there are dishonest people in science. Punishing a fraudster does not change the selective environment that made a particular kind of research profitable. His account also gives scientific success an awkward role in the story. As Zhou put it on Saturday, science became a victim of its own success. Once research became central to industry, national power, and economic growth, universities and laboratories expanded, and public money followed. That created an administrative need for rapid decisions: who should get the next grant, the next laboratory, the next appointment? The difficulty is that the true value of a discovery may take years or decades of testing and building to become clear. Resource allocation cannot wait that long. Publication counts, journal prestige, impact factors, and citations therefore become convenient ways to make an instant judgement. “The real problem is not that these indicators have no value,” Wang Xiaodong writes, “but that they are trying to answer a question that only time can answer.” Telling administrators simply to stop counting papers will never be enough. They still have budgets to distribute and appointments to make. Something has to replace the shortcut. Zhou described the consequences inside publishing. Papers acquire ever more requirements: a complete story, polished presentation, extensive datasets, and accessibility to readers beyond the immediate field. Individually, those demands sound reasonable. Together, he warned, they produce formulaic “eight-legged” papers 八股文 and rigid reviewing, while genuinely original or non-consensus work struggles to get past journal editors—some of whom wield immense gatekeeping power despite having limited laboratory experience themselves. Meanwhile, the demands for sprawling, “complete” narratives have fuelled a wider replication crisis. Wang Xiaodong uses a mahjong metaphor to describe the result: put the complex papers published by the exact same lab over several years side by side, and they often look like “Thirteen Orphans” (十三不靠)—every tile completely unrelated to the next, and none of them reproducible by outsiders. Zhou also spoke frankly as an editor who has trouble finding reviewers. Everyone wants someone else to review their work; qualified senior researchers have little time to return the favour. The labour is anonymous, unpaid, and brings almost no institutional recognition, so it increasingly gets passed down to postdocs and graduate students. And while anonymity protects reviewers from rank and personal favours, hyper-specialisation means an author’s most qualified reviewer is often a direct competitor, shielded from accountability. The protection and the problem coexist. Wang Liming takes the argument a step further. The decisive change, in his essay, is the instant conversion of academic honour into material resources. Once a paper can be cashed in for funding, a job, students, commercial investment, or even a company valuation, scientists are alienated from their work: they must keep minting this “research currency” to keep their teams alive. He is careful not to romanticise the past. The old world of gentleman scientists—financially independent figures like Boyle and Darwin who needed nothing from external funders—was also a closed club that excluded people without inherited wealth, women, and much of humanity outside the West. Professional science allowed ordinary people, himself included, to become researchers. Nobody should want to undo that. The problem, in his account, is an exchange system that becomes too uniform and too difficult to correct. His most pointed Chinese example is the “hat” (帽子): the prestigious talent designation that brings continuing access to money, laboratory space, students, and institutional influence. “If papers are the circulating currency of the research system, then a ‘hat’ is a bond that pays interest over the long term,” he writes. A paper at least requires another round of peer review. A title in the Chinese context can lock in a judgement made years ago and turn it into permanent status rent, regardless of whether its holder is still doing good science. Here, official institutions hire, organise, and evaluate scientists. Unlike honours awarded by autonomous academic communities in the West, a Chinese “hat” blends non-scientist administrative power with state authority. Once granted, it turns a past judgement into permanent status rent that is nearly impossible to revoke—because taking a hat off would imply that official authority erred in putting it on. Both Wangs see China as experiencing, at compressed speed, pressures present across global science. Research expansion, rising investment, publication growth, and elaborate evaluation metrics arrived in China within two or three decades rather than two or three centuries. Zhou agreed with that international framing—noting that recent US White House science policy documents and the new president of the US National Academy of Sciences, a fellow palaeontologist who recently visited Zhou’s institute in Beijing, have raised strikingly similar warnings about consensus-bound peer review, short-term project grants, and the replication crisis. Still, Zhou emphasised that China’s traditional hierarchy, personal networks (guanxi), and the ethos that “a good scholar becomes an official” (学而优则仕) amplify those pressures at home. So what would change things? Here Zhou’s tone differed from the call for a revolution in scientific trust in Wang Xiaodong’s essay. As an evolutionary biologist, Zhou favoured patchwork repair (修修补补). Living systems survive through accumulated adjustments; dramatic mutations are usually fatal. Science cannot return to a small, slow-moving pastoral era, especially after the successive accelerations of professionalisation after the Second World War, the internet, and now artificial intelligence. But it can alter the local environment in which researchers work. He pointed to domestic experiments designed to support unconventional research and diversify funding, including Tencent’s New Cornerstone Investigator Program, the Xplorer Prize, and the Future Science Prize. He also mentioned participating in reviews for “major non-consensus projects” under the National Natural Science Foundation of China. One guiding principle he recalled was wonderfully direct: “Failure is allowed; corruption is not” (允许失败，不允许腐败). That distinction would mean quite a lot if taken seriously. An honest attempt that fails should not have to disguise itself as a success to survive an assessment. Wang Liming’s essay adds a sharp caveat to the optimism about new domestic funders. Multiple organisations do not automatically produce multiple ways of judging science. If the same pool of senior domestic scientists makes the decisions through the same two-round review procedures, it is still “fake diversity.” He argues for three distinct kinds of money: broad baseline funding governed by fair procedures; patient funding for questions that take ten years; and non-consensus funding based on individual taste, deliberately empowering a few genuine experts to make biased, contrarian bets on eccentric ideas that would inevitably be averaged out by a committee. Replacing one monopoly with another achieves little; a healthy ecosystem needs variance. Zhou’s proposals for publishing were similarly concrete: strip papers of their resource-allocation burden and return them to recording discoveries and establishing priority; separate dissemination from evaluation, as eLife and Peer Community In do; adopt more modular “micro-publications” and real-name endorsements; recognize the labour of editors and reviewers; and give replication work proper credit rather than treating it as an unpublishable dead end. AI makes every part of this debate more urgent—and Zhou wove it throughout his talk. In his own preparation, he used AI to survey the declining influence of academic monographs, noting how tools are already changing how scholars gather information. More fundamentally, he placed AI as the latest great acceleration in scientific history: just as the internet sped up the pace of research and tightened external resource pressures, AI is compressing the cycle again. In the essays Zhou cited, AI cuts both ways. Wang Xiaodong expects large language models to erase much of the English-writing disadvantage long faced by Chinese scientists, further swelling the flood of papers coming out of Chinese labs. Wang Liming sees AI accelerating both ends of the trust crisis: it lowers the cost of paper mills and fabricated images just as quickly as it lowers the cost of automated image forensics, data auditing, and code reproduction. “Whoever builds the verification layer wins,” Wang Liming writes. His proposed alternative to the static, packaged “story paper” is a continuously versioned “unit of discovery” containing a falsifiable claim, raw data, analysis code, experimental parameters, and an ongoing log of independent checks—where negative results and failed replications are recorded rather than buried. Zhou ended his keynote by bringing AI back to the question of scientific honour and credit. Citing a recent Intellectual discussion on “What AI Means for Mathematics” featuring Fields Medalist Deng Yu 邓煜—at a moment when AI is already batch-solving mathematical conjectures, as HKU Vice-President Lin Chen noted in his opening remarks—Zhou agreed that human researchers must remain the principal agents: AI is a tool that frees scientists from tedious calculation to think about deeper, messier real-world problems. Yet that partnership creates a thorny new evaluation problem. When a breakthrough is made with AI, what is the human contribution and what is the machine’s? And since AI models distil centuries of accumulated human scholarship, is it right that the credit and value flow so heavily to the private AI companies building the tools? The old struggle over how to assign scientific honour is acquiring a whole new layer. What I took away was a serious discussion of how science can remain trustworthy as its scale, incentives, and tools change. These were scientists with real standing inside China’s system questioning how that standing is produced, and proposing changes that would affect their own institutions and peers. That made the afternoon at HKU’s Beijing Centre worthwhile. At the close, Wang Feng, Director of Communications and Public Affairs at HKU, said the value of the forum series—which heads to Hangzhou in December and cities like Chengdu early next year—would lie in the real cooperation it helped bring about. The university has plenty to celebrate: this week it topped the QS Asia rankings for a second consecutive year, alongside its 11th-place position in the QS World University Rankings 2027. For me, bringing this debate to an audience beyond the people who review papers and allocate grants was a useful contribution. Share [ The East is Read PhD dropout’s exposé forces an academic fraud reckoning in China A former doctoral student turned blogger has shaken China’s academic establishment by publicly accusing prominent university scholars of fabricating data and manipulating papers, triggering investigations at several leading institutions and drawing rare attention from state media… Read more 5 months ago · 43 likes · 8 comments · Yuxuan JIA ](https://www.eastisread.com/p/phd-dropouts-expose-forces-an-academic?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=47580)
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Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. 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