The theoretical foundation of the study comes from the social psychologist Serge Moscovici, who developed the Theory of Social Representations by building on Émile Durkheim’s earlier notion of collective representations. A social representation is a shared reconstruction of reality, shaped by the dominant norms, values, and ideologies of a society, and it arises through interpersonal interaction and communication. Where money attitudes describe an individual’s personal beliefs, emotions, and behavioral inclinations, social representations frame money as a social object, embedded in a constellation of relationships with saving, debt, investment, trust, and politics, and evolving over time as new events are assimilated. This distinction matters because attitudes do not form in a vacuum: they grow out of a cultural, historical, and economic framework that the collective supplies in advance.

The authors identified three gaps in the existing literature that their study was designed to fill. First, most psychological research on money has focused on attitudes rather than on the social representations that underpin them. Second, the field has relied overwhelmingly on quantitative methods with closed-ended questions, which reveal little about how specific money attitudes form in context. Third, genuinely cross-cultural and cross-national comparisons remain scarce, even though evidence shows that culture shapes how people perceive and categorize monetary resources. In many Western societies money is closely associated with autonomy and personal achievement, whereas in several Asian countries it is more often linked to relational and familial obligations, respect, and ethics. Earlier work in France by Vergès found that work and well-being anchored the representation of money, while a study in Turkey placed work in a more peripheral position, hinting at meaningful cultural variation.

Italy and the United States made an intriguing comparison because they share some cultural traits while diverging sharply on others. Both score similarly on individualism and on perceptions of power equality, yet they differ in willingness to accept uncertainty, time orientation, and indulgence. Italians tend to experience more stress and anxiety when facing unpredicted events, adapt traditions to circumstances, and encourage thrift, while Americans are more flexible in the face of challenges, focus on the present, and report higher happiness and life satisfaction. The economic backdrop also diverges: the United States has outperformed Italy in GDP growth in recent decades and recovered more strongly from the pandemic, while Italy continues to struggle with unemployment rates among the highest in Europe, trailing only Greece and Spain. The two welfare systems differ too, with Italy’s conservative-corporatist model tying benefits to employment and family support, and the American liberal model emphasizing individual responsibility and means-testing.

Methodologically, the researchers used the free association technique, the classic instrument of social representation research. Between March and May 2022 they collected data from 305 Italian participants, and by December 2022 they had gathered 515 participants in the United States, all recruited through an online panel and surveyed via Qualtrics. Each participant was asked to write up to ten words or expressions that came to mind when thinking about money, then to assign a positive, neutral, or negative valence to each one. They also completed three validated scales: the Financial Threat Scale, measuring fear and uncertainty about financial security; a Financial and General Vulnerability scale, assessing the likelihood of future hardship; and the Multidimensional Subjective Financial Well-being Scale, capturing satisfaction with one’s current financial situation. The Italian protocol was approved by an ethics committee at Università Cattolica, and the American protocol by Kansas State University’s research compliance office.

The analysis proceeded in three steps. A prototypical analysis, run with the IRAMuTeQ software, applied Abric’s Central Core theory, which holds that a social representation has a dual structure: a central core embodying its essence, and a peripheral zone reflecting individual differences and more adaptable meanings. Words were grouped semantically and plotted by frequency and mean rank of evocation, with lower ranks indicating greater salience. A correspondence analysis using the HOMALS procedure then mapped the associations in a two-dimensional space, and finally correlational analyses linked the resulting dimensions and emotional valence to the financial scales. A diversity index, computed by dividing the number of distinct terms by total occurrences, gauged the level of consensus in each sample.

The Italian results revealed a representation organized around abstract, symbolic values. The word money elicited 302 different associations with a mean valence of 0.31, and the most frequent responses were Work, cited by 21 percent of respondents, followed by Peacefulness at 16 percent, Well-being at 15 percent, Expenses at 15 percent, and Necessity at 13 percent. The prototypical structure placed Work and Well-being in the central core, with negative concepts entirely absent and only neutral terms such as Expenses, Necessity, and Cash in the periphery. The correspondence analysis produced two axes: a horizontal one contrasting an instrumental perspective, anchored by words like coins, paper money, cash, and wage, with a symbolic perspective marked by peacefulness, autonomy, freedom, and power; and a vertical one contrasting an individual dimension of daily practices such as effort, free time, saving, and investment with a universal dimension evoked by richness and poverty. Correlations showed that Italians who attributed a more positive valence to money reported less financial threat, less vulnerability, and higher subjective financial well-being.

The American picture was strikingly different in content, though structurally parallel. Money evoked 462 different associations with a higher mean valence of 0.42 and a diversity index of just 0.13, indicating strong consensus. The most frequent associations were Cash, cited by 25 percent of respondents, Necessity at 21 percent, Bills at 20 percent, Happiness at 19 percent, and Saving at 19 percent. The central core contained four elements, two tangible, Cash and Bills, and two psychological, Necessity and Happiness, while the periphery was dominated by pragmatic terms such as Saving, Paying, Salary, Funds, and Investing, with abstract words like Life, Power, and Importance relegated to the distant periphery. The correspondence analysis again yielded instrumental and symbolic poles, and individual and universal dimensions, but the overall image was of money as a practical, functional tool whose centrality to happiness is taken for granted. In the American sample, a more positive valence correlated strongly with higher subjective financial well-being and with lower perceived financial threat.

The convergence in structure alongside divergence in content is the study’s most theoretically interesting result. In both countries, money proved to be a polymorphous object, simultaneously symbolic and utilitarian, individual and universal. But the emotional center of gravity differs: Italians defend an abstract, strongly symbolic vision in which money connects to work, security, freedom, and long-term well-being, and their outlook is more ambivalent and cautious, consistent with earlier Italian studies that found negative visions of money centered on job loss, uncertainty, and fear of the future. Americans, by contrast, hold a pragmatic, positive representation in which money determines happiness, echoing prior cross-national research showing that Americans attribute more importance to money than Europeans do, and even Alexis de Tocqueville’s observation in 1835 that love of wealth lies at the bottom of the actions of Americans. The authors interpret the difference as a reflection of both economic conditions, with Italian unemployment making work central to the meaning of money, and cultural values, with American individual responsibility fostering a transactional view of money as the key to immediate satisfaction.

The practical implications reach into financial education and professional practice. In Italy, the authors suggest, financial education should foster a more constructive vision of money as a tool for achieving meaningful goals, emphasizing long-term security and the link between financial habits and quality of life. In the United States, programs should encourage a shift from a transactional state of happiness toward more stable well-being, helping people recognize the risks of equating money with happiness. Across both countries, the findings argue for moving beyond basic financial literacy to address the psychological dimensions of money, using strategies such as journaling, group discussion, and values-clarification exercises, since objective knowledge alone seldom changes behavior. Financial planners and mental health practitioners alike can use these insights to surface clients’ underlying beliefs about money. The authors caution that their samples were not nationally representative and that social representations are snapshots of a precise historical moment, calling for longitudinal replications in more diverse cultural settings. Even so, the message is clear: money means different things in different places, and any policy or education that ignores those shared meanings risks missing the point entirely.

Subject of Research: Cross-national comparison of social representations of money in Italy and the United States

Article Title: Thinking About Money: Cross-national Comparison of Social Representations of “Money” in Italy and the United States

Article References: Sesini, G., Gray, B., McCoy, M., Seay, M., & Lozza, E. (2026). Thinking About Money: Cross-national Comparison of Social Representations of “Money” in Italy and the United States. Trends in Psychology. https://doi.org/10.1007/s43076-026-00518-7

Image Credits: AI Generated

DOI: 10.1007/s43076-026-00518-7

Keywords: social representations, money psychology, economic psychology, cross-cultural comparison, Italy, United States, free association, financial well-being, money attitudes, financial education, Serge Moscovici, happiness

Triple-negative breast cancer, which lacks the three molecular targets exploited by modern targeted therapies, accounts for roughly 10 to 15 percent of all breast cancers but is diagnosed at more advanced stages and offers fewer effective treatment options than other subtypes. It disproportionately strikes women under 40, women with BRCA1 mutations, and Black women, who are diagnosed at twice the rate of women of any other racial or ethnic background. Because clinical trials have driven nearly every recent advance in the disease’s treatment, including the landmark pembrolizumab studies that reshaped care within the last five years, equitable access to those trials is not an abstract concern. It is the mechanism by which scientific progress translates into longer lives.

To build their national picture, the researchers queried ClinicalTrials.gov as of September 30, 2024, sifting through all 510,397 registered studies to isolate active phase II and phase III interventional treatment trials specific to triple-negative breast cancer. After excluding non-cancer studies, studies without U.S. sites, and trials no longer open to enrollment, they identified 108 active trials, 58 for metastatic disease and 50 for non-metastatic disease, supported by 1,230 trial sites across the country. Each site was assigned to a U.S. county through spatial join analysis, and the resulting tabulations were overlaid with county-level data from the U.S. Census Bureau, the U.S. Department of Agriculture’s rural-urban continuum codes, the Centers for Disease Control and Prevention’s Social Vulnerability Index, and the U.S. Climate Vulnerability Index’s baseline health vulnerability scores.

The headline numbers are sobering. Of the nation’s 3,144 counties, 76.2 percent had no available triple-negative breast cancer trial whatsoever. Only 12.4 percent had exclusively federally sponsored trials, 9.7 percent had both federally and non-federally sponsored trials, and a mere 1.7 percent relied solely on industry or other non-federal sponsors. Yet the picture is not uniformly bleak: 78 percent of the roughly 124 million U.S. women aged 18 and older lived in a county with at least one trial available, and another 17 percent had access in an adjacent county. The problem is concentrated in specific, identifiable populations, and the study’s county-level breakdown reveals exactly where the trial network frays.

Rural America sits at the sharpest edge of the disparity. Trials were available in just 9.8 percent of rural counties compared with 47.0 percent of metropolitan counties, a difference the authors report as highly significant. And among the rural counties that did host trials, 80 percent offered exclusively federally sponsored studies, compared with only 42 percent of metropolitan counties with trials. In other words, the federal clinical trials infrastructure, including the National Cancer Institute’s National Clinical Trials Network, is effectively the sole lifeline keeping rural women connected to experimental treatments. Any contraction in federally sponsored research, the authors warn, would have uniquely devastating consequences for rural patients, whose cancer mortality rates, including ten-year breast cancer mortality, are already known to exceed those of their urban counterparts.

Health vulnerability tells a parallel story. Counties in the highest quartile of the Climate Vulnerability Index’s baseline health vulnerability measure, reflecting burdens of chronic disease, limited access to care, and poorer preventive health, were significantly less likely to have any available trial: 88.3 percent had none, compared with 72.2 percent of counties in the lower three quartiles. Among counties with trials, 73 percent of the most health-vulnerable depended exclusively on federal sponsorship, versus 50 percent of less vulnerable counties. Social vulnerability showed a similar, though somewhat attenuated, gradient, with 78.6 percent of the most socially vulnerable counties lacking any trial. This mirrors a broader pattern in American oncology, where 94 percent of all cancer trial sites are located in areas more affluent than the national average.

Race and ethnicity shaped the map as well. Among counties with predominantly non-Hispanic White populations, 75.8 percent had no triple-negative breast cancer trial, compared with 79.1 percent of predominantly Hispanic counties, 81.5 percent of predominantly Black counties, and a striking 96.9 percent of predominantly American Indian and Alaska Native counties. But the researchers caution that county-level racial predominance does not necessarily reflect where members of each group actually live. When they analyzed access at the population level instead, most Black women, 82.1 percent, and Hispanic women, 86.5 percent, resided in counties with an available trial, while access dropped to 63.5 percent among American Indian and Alaska Native women and rose to 93.5 percent among Asian and Pacific Islander women. The divergence between county-level and population-level measures, the authors argue, underscores the need to evaluate trial access through both lenses.

Regional disparities compound the inequity. Ten percent of women in the South, more than five million people, lacked access to a triple-negative breast cancer trial in either their home county or any neighboring county, compared with just 1 percent of women in the Northeast. This is particularly troubling because the South carries the heaviest burden of new triple-negative breast cancer diagnoses in the country, accounting for 40 percent of cases, more than the Northeast and West combined. Two-thirds of Southern counties had a trial available, versus 87 percent of counties in the Northeast and West. Meanwhile, metastatic trials, the studies most relevant to patients with advanced disease, were scarcer than early-stage offerings: only 63 percent of trial sites had metastatic trials, and just 9.4 percent of metastatic trial sites offered four or more options, limiting both proximity and choice for the women who need trials most urgently.

The study’s findings arrive amid a broader reckoning with the representativeness of cancer research. Trial participants have historically been younger, healthier, and less racially, ethnically, and geographically diverse than the patients who ultimately receive the resulting therapies. Prior work by some of the same investigators found that 70 percent of all U.S. counties lacked any cancer treatment trial and that 51 percent had neither research nor oncology care sites. Survey data cited in the new paper show that only 37 percent of patients actively undergoing cancer treatment are willing to travel for a trial, yet more than half of women with metastatic breast cancer report driving over an hour to reach a trial site. When comparable trial options are available to rural and urban patients alike, studies suggest, the survival gap between them narrows or disappears, making geographic access a modifiable determinant of outcome.

The authors point toward concrete remedies: pragmatic and decentralized trial designs that reduce the burden of participation, expanded eligibility criteria to ensure results generalize to real-world populations, and technologies such as telemedicine and remote monitoring that can decouple enrollment from physical proximity. They also emphasize the outsized importance of sustained federal investment in programs like the NCI Community Oncology Research Program and the National Clinical Trials Network, which extend trial infrastructure into community settings. The analysis has limitations, including its reliance on manually entered ClinicalTrials.gov data and its descriptive, county-level design, which cannot establish causation or capture individual enrollment decisions. Still, as the first study to chart the geography of triple-negative breast cancer trials against the demographics of the women they are meant to serve, it offers government agencies, industry sponsors, and hospital systems a data-driven roadmap for deciding where the next trial site should open, in a disease where novel treatment strategies are urgently needed and every mile between a patient and a protocol can matter.

Subject of Research: Geographic access to triple-negative breast cancer clinical trials in the United States

Article Title: Geographic access to triple negative breast cancer clinical trials: are trials located near patients?

Article References: Amin, L. B., Kirkwood, M. K., Levit, L. A., Balogh, E. P., Waterhouse, D. M., Unger, J. M., Garrett-Mayer, E., & Chavez-MacGregor, M. (2026). Geographic access to triple negative breast cancer clinical trials: are trials located near patients?. Breast Cancer Research and Treatment, 219(3), Article 22. https://doi.org/10.1007/s10549-026-08084-3

Image Credits: AI Generated

DOI: 10.1007/s10549-026-08084-3

Keywords: triple-negative breast cancer, clinical trials, health disparities, geographic access, rural health, health equity, ClinicalTrials.gov, National Cancer Institute, social vulnerability, breast cancer mortality, trial sponsorship, United States

The timing of the analysis is significant. In 2025, China became unprecedentedly tough in the trade war launched by the Trump administration, with mutually announced retaliatory tariffs spiraling to 145 percent in April, a level that, if implemented, would have meant complete economic decoupling between the world’s two largest economies. The technology war intensified in parallel: while the United States continued to tighten its chip trade embargo, China responded with export controls on rare earths, a sector where it holds dominant global processing capacity. In early September, China put forward a Global Governance Initiative at the Shanghai Cooperation Organization Summit, held a grand military parade marking the 80th anniversary of the victory in the anti-fascist war, and announced that it would no longer seek the special and differential treatments reserved for developing countries in future World Trade Organization negotiations. Taken together, these actions appeared to signal a firm belief in Beijing that the world is moving inexorably toward multipolarization.

Yet the historical record that Jing traces suggests continuity rather than rupture. Since the post-1978 reform and opening up, China’s global strategies have been formed and carried out under a global framework dominated by the United States. China was, on the whole, a user, defender and reformer of the post-war order, experiencing gradual learning, integration and innovation that made it a deep stakeholder in the system. The phrase balance of financial terror was coined to describe the irreversible interdependence formed between the two countries, even though China was clearly the weaker party. Under that power asymmetry, Beijing typically adopted what the paper describes as a swallow anger and keep quiet attitude toward American provocations and sanctions, including the 1999 bombing of the Chinese Embassy in Yugoslavia by five American precision-guided missiles. Deng Xiaoping’s dictum to keep a low profile and never take the lead governed Chinese diplomacy for decades, even as successive leaders from Jiang Zemin’s peaceful rise to Hu Jintao’s harmonious world signaled growing awareness of China’s global role.

The shift in the relationship came in stages. China’s entry into the WTO in 2001 embedded it in existing governance structures, and its cooperation with the United States at the first G20 summit in Washington in 2008 helped stabilize the global financial order. But as China’s GDP surpassed Japan’s in 2010 and incremental development within the existing trade framework ran into limits, Beijing proposed the Belt and Road Initiative in 2013 and led the creation of the Asian Infrastructure Investment Bank and the New Development Bank. These China-led mechanisms, which the United States declined to join and warned its allies against joining, augmented American tension. During Trump’s first term, containment of China became a basic consensus of both American political parties and the elite, forging what the paper, citing Graham Allison, frames as a Thucydides trap, manifested not only in the trade war but also in the small yard and high fence technology restrictions of the Biden administration. American pressure in turn fortified China’s determination to strengthen autonomy and reduce dependence on the United States, economically and technically.

The first dimension of Jing’s framework, comprehensive national strength, provides the material foundation for this strategic posture. Between 2000 and 2021, China’s total economic output measured by GDP rose from approximately 11.8 percent of the US level to 76 percent, according to World Bank data cited in the study, and although the ratio fell back to 64.7 percent in 2023, China’s growth rate remains significantly higher. In purchasing power parity terms, IMF figures show China’s economy surpassed that of the United States in 2014. China is the world’s largest trading country, the primary manufacturing base, the second largest foreign investor, and the only competitor of the United States in artificial intelligence, with the China-based DeepSeek large language model appearing just one year after ChatGPT. Ironically, the paper notes, China’s success within the existing system, particularly the WTO, has been a source of Trumpism’s antipathy toward the very institutions the United States built after World War II.

China’s tough but restrained responses to the tariff and tech wars, Jing argues, can be explained by three pragmatic concerns. First, Trumpism challenges fundamental interests of China’s national development: the trade war could raise the costs of Chinese manufacturing across the board, while sanctions on high-tech enterprises, including the 2018 detention of Huawei CFO Meng Wanzhou in Canada and steadily tightening chip export controls, could seriously damage China’s development in advanced fields at a time of sluggish real estate growth, tight employment, mounting local debt and aging pressures. Second, the two economies remain deeply interdependent, in a way fundamentally different from the mutually divided systems of the Cold War. When China announced strict rare earth export controls on October 9, Trump immediately threatened an additional 100 percent tariff effective November 1, illustrating how quickly each side is made aware of its exposure. Third, maintaining the existing international economic system is beneficial to China, which must continue reorganizing its industrial, supply and value chains on a global scale and therefore has an interest in countering trade protectionism and safeguarding multilateral trade.

The second dimension, institutional learning and innovation, shows how China’s engagement has deepened over four decades. China restored its membership in the World Bank and IMF in 1980 and gradually expanded its influence and voting rights, then established the New Development Bank in Shanghai in 2014 with an equal-investment governance structure, and the AIIB in Beijing in 2015, modeled on the World Bank. The AIIB now counts 110 members, including every permanent member of the Security Council except the United States and 16 G20 countries. In climate governance, the 2015 Paris Agreement rested substantially on Sino-American cooperation, and after Trump first exited the accord, China reconfirmed its commitments and held cooperative dialogues with the European Union, later pledging at the 75th UN General Assembly to peak carbon emissions by 2030 and achieve carbon neutrality by 2060. The paper observes an irony: China has become a defender of the current international system while the United States has become a dismantler.

The third dimension concerns crisis-induced windows of opportunity. Past global shocks have repeatedly strengthened China’s position: the 1997 Southeast Asian Financial Crisis and the 2007 Global Financial Crisis both improved China’s standing in global economic governance. Trumpism itself, with its American centrism, transactional approach and disregard of rules, constitutes a crisis of global governance that aggravates governance deficits and raises world expectations for Chinese responsibility. Global impressions of the two countries have shifted in opposite directions, and Trump’s second-term win contributed to negative votes against pro-Trump candidates in Canadian and Australian elections. When the Trump administration withdrew from international organizations and agreements, China consolidated its position within the United Nations system and affirmed its commitments, with its four major global initiatives since 2021 each carrying distinct Chinese values and norms.

The conclusion Jing draws is that China’s responses to Trumpism will continue to promote gradual reforms of the global governance system, while relations with the United States move toward mutual assurance on an equal footing. The meeting between Presidents Xi and Trump in Busan on October 30, 2025, and a follow-up call on November 24, indicated a strategic compromise born of Trump’s informed awareness of China’s will and capability, with a provisional one-year ceasefire suggesting a higher chance of a grand bargain and reviving speculation about a G2-based global order. Yet the paper warns that the shift of global power will not be smooth or even peaceful, and that reckless pursuit of unrealistic goals by either side could bring unforeseen crisis moments. Jing further suggests that China’s incremental domestic reform philosophy, which starts from local experiments and seeks Pareto improvements rather than zero-sum outcomes, has been naturally extended to its global strategies, making China’s engagement continuous, adaptive and irreversible. Achieving effective mutual understanding and coordination between the rising and the established power, the analysis concludes, will be the biggest variable in the future of global governance.

Subject of Research: China's global governance strategies under US Trumpist foreign policy pressures

Article Title: Trumpism and China’s global strategies: a tipping point?

Article References: Jing, Y. (2025). Trumpism and China’s global strategies: a tipping point?. Global Public Policy and Governance, 5(4), 401-410. https://doi.org/10.1007/s43508-025-00138-4

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00138-4

Keywords: Trumpism, China, United States, global governance, trade war, tariffs, US-China relations, Belt and Road Initiative, AIIB, multilateralism, Thucydides trap, incremental reform

Arrighi, who taught at the State University of New York at Binghamton’s Fernand Braudel Center and later at Johns Hopkins University, built his theory in dialogue with the founders of dependency theory and world-systems analysis, including Andre Gunder Frank and Immanuel Wallerstein. The starting point of that tradition is deceptively simple: states cannot be understood in isolation. The world is a single, unified system in which economic actors, above all corporations, have become political actors in their own right, often more powerful than the nation-states that host them. Within this system, some nations occupy the core while others are pushed to the periphery, and the relationship between the two is not accidental but structural.

Frank’s version of dependency theory, developed in the 1960s, described the mechanism in starkly extractive terms. Core powers draw raw materials and cheap labor from peripheral nations, process them into finished goods, and sell those goods back at high prices, flooding local markets and preventing indigenous industry from developing. Underdevelopment in the periphery, in this account, is not a failure to modernize but the very condition that makes development in the core possible. Colonial monocultures, such as tea cultivation in India, and later mechanisms like production relocation and international loans, all served to lock peripheral economies into dependency. Latin American critics of the theory, from Ruy Mauro Marini to Theotonio dos Santos, went on to identify escape routes: building domestic industry behind protective walls, detaching from a weakening hegemon, or pursuing revolutionary rupture.

Wallerstein took these insights and scaled them up. In his four-volume The Modern World-System, he replaced the dyadic core-periphery model with a tripartite structure that included semi-peripheral countries such as Brazil, India and China, states that aspire to core status and progressively move closer to it. Drawing on Marx’s analysis of capitalism and Fernand Braudel’s attention to long-term processes, Wallerstein distinguished centralized world-empires, which extract taxes from their peripheries, from the decentralized capitalist world-system that emerged in the sixteenth century, in which the periphery supplies cheap raw materials and labor while the core monopolizes high-value production. It was within this intellectual milieu that Arrighi developed his own distinctive contribution.

Arrighi’s masterwork, The Long Twentieth Century, first published in 1994, proposed that the history of capitalism unfolds in a series of systemic cycles of accumulation stretching back to the fifteenth century. Each cycle begins with the productive expansion of capital, money invested in commodity production, described by the Marxian formula M-C, and ends when overaccumulation sets in and a signal crisis marks the turning point. At that moment capital retreats from production into finance, the C-M’ phase, and the accumulated wealth is lent out to finance the next cycle, typically under new leadership. Arrighi identified four such long centuries: the Genoese cycle from the late fifteenth to the early seventeenth century, the Dutch cycle through the mid-eighteenth century, the British cycle through the late nineteenth century, and the American cycle, whose signal crisis arrived in the 1970s amid the Vietnam War and the collapse of the Bretton Woods monetary order.

The pattern behind these cycles is remarkably regular. Each hegemonic power operates on a progressively larger state scale, from the city-state of Genoa to the Dutch Republic, the British Empire and the American world system. Some cycles, notably the Genoese and British, are characterized by extensive development, while the Dutch and American cycles show intensive development. Over time, hegemonic powers internalize more functions: Genoa remained a purely commercial republic, while later powers secured their own protection, production and transaction costs. Crucially, in each transition the declining hegemon becomes a creditor to its successor, financing with its accumulated capital the very power that will displace it. Arrighi saw exactly this dynamic in the relationship between the United States and China: after China’s entry into the World Trade Organization, its export-led industrial expansion generated financial power sufficient to help finance American external debt.

In Adam Smith in Beijing, published in 2007, Arrighi turned to the shift in the epicenter of capital accumulation toward East Asia. China’s rise, in his reading, was the result of deliberate policies that moved the country from semi-peripheral status toward an economic model capable of challenging American primacy, based on industrial production for export at precisely the moment when Western economies were deindustrializing and offshoring. Trumpism, in Imbriano’s analysis, is best understood as an attempt to interrupt this process: a repositioning of American military and commercial power in the Western hemisphere, an authoritarian shift within the liberal system, and a concerted effort to curb the economic and military ascent of China. Its two key instruments are disengagement from distant conflicts and an intensification of pressure, through NATO’s eastern expansion in Europe and through the trade war against Beijing.

Yet the study finds that this response appears insufficient. The threat of tariffs has not redirected the economic strategies of American competitors, and the attempt to revive industrialization on American soil faces formidable obstacles. The evidence from Latin America illustrates the difficulty: trade between the region and China has grown substantially in recent decades, and China’s Belt and Road Initiative has supported infrastructural development that reduced Latin American dependency on the United States, even if the relationship still reproduces a pattern of raw material exports and manufactured imports that has not always fostered local industry. Meanwhile, European allies bound to Washington find themselves pressured to curtail economic ties with Asian partners and Russia, a course that conflicts with their own development interests.

Arrighi identified two anomalies in the current transition that make it unlike any previous one. First, the economic power of the emerging hegemon is separated from the military power of the declining one, a configuration without precedent in earlier cycles. Second, the new leading power may develop its accumulation in a form that is not capitalist in the conventional sense, opening the possibility, in Arrighi’s optimistic reading, of a system based on mutual respect between civilizations and a genuinely multipolar world order. But this outcome presupposes that the United States accepts its transition peacefully. In Chaos and Governance in the Modern World System, written with Beverly Silver in 1999, Arrighi warned that transitions can stall, degenerate into prolonged systemic chaos, or be governed through war. The study concludes that Trumpism, as a product of hegemonic crisis, leaves both paths open: a negotiated multipolar order of peace, or a new systemic chaos of financial and military tension among competing regional powers. Which of these futures prevails, the analysis insists, is not mechanically determined, and that open question is precisely what makes Arrighi’s long view of capitalism so illuminating for the present.

Subject of Research: Applying Giovanni Arrighi's world-systems theory of hegemonic transitions to Trumpism and the crisis of United States global hegemony

Article Title: Trumpism, the world system and multipolarism: a perspective from Giovanni Arrighi’s thought

Article References: Imbriano, G. (2025). Trumpism, the world system and multipolarism: a perspective from Giovanni Arrighi’s thought. Global Public Policy and Governance, 5(4), 329-339. https://doi.org/10.1007/s43508-025-00135-7

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00135-7

Keywords: Giovanni Arrighi, Trumpism, world-systems theory, hegemonic transition, multipolarism, United States, China, dependency theory, Immanuel Wallerstein, global governance, systemic cycles of accumulation, American decline

The research team conducted large-scale randomized survey experiments on representative samples of non-Indigenous adults in Australia, with 1,724 participants, and the United States, with 1,773 participants. In these experiments, respondents were randomly assigned to read a land acknowledgement or a comparable text without the acknowledgement, allowing the researchers to isolate the causal effect of exposure. This design matters because most previous claims about land acknowledgements, in either direction, rested on correlational evidence or theoretical argument. By randomly assigning exposure, the researchers could measure whether the statements themselves shift awareness, attitudes, or political preferences, rather than merely observing that people who like land acknowledgements also hold particular views.

The findings on awareness are the clearest positive result. Exposure to a land acknowledgement measurably increased participants’ awareness of local Indigenous groups, confirming one of the central claims made by proponents. In a society where Indigenous presence has historically been erased from public space, the simple act of naming the traditional custodians of the land does appear to convey real information to audiences. For institutions hoping that a land acknowledgement at least teaches people something about whose land they occupy, the experiments offer support. The effect is modest but genuine, and it held across both the Australian and American samples, suggesting the mechanism is not unique to the country where the practice originated.

Yet the same experiments produced a result that advocates will find harder to celebrate: exposure to land acknowledgements reduced participants’ interest in Indigenous culture and heritage. Rather than inspiring curiosity or engagement, the statements appear to have functioned as a kind of closure, a ritual that signals the relevant box has been checked. The researchers suggest this pattern is consistent with the idea that symbolic recognition can satisfy a psychological need for moral completeness, leaving audiences less motivated to learn more. If a land acknowledgement tells people that Indigenous presence has been duly recognized, the implicit message may be that no further personal engagement is required. This backfire effect on cultural interest is among the most striking findings of the study and raises difficult questions about how such statements are framed and delivered.

On the political questions that matter most to proponents, the results were null. The experiments found no significant effects of land acknowledgement exposure on a range of attitudes, including collective guilt for historical wrongdoing and support for reparations. This null result is substantively important. The theory underlying many land acknowledgements holds that recognition is a first step on a path toward material redress, that naming dispossession cultivates the moral emotions and political will needed for compensation and structural reform. The experimental evidence does not support that causal chain, at least in the short term and for the general non-Indigenous public. Hearing that an event is taking place on the land of a particular Indigenous nation did not make Australians or Americans more willing to back financial reparations or other corrective policies.

The study went beyond audience effects to examine the incentives facing the institutions that adopt these practices. In a second set of experiments involving 3,638 participants, the researchers tested how the adoption of land acknowledgements affects public perceptions of organizations, particularly institutions facing scrutiny over their treatment of Indigenous peoples. The results showed that adopting a land acknowledgement provides small but real reputational benefits, improving assessments of an organization’s corporate social responsibility. In other words, the practice works, at least modestly, as a reputational signal for the organizations that perform it. This finding aligns with long-standing theories in sociology about institutional isomorphism, the process by which organizations in a field adopt similar practices to maintain legitimacy, and with signaling theory, which treats costly and symbolic displays as information about an actor’s qualities.

Crucially, the reputational payoff of land acknowledgements paled next to that of costlier actions. When the researchers compared symbolic statements with substantive practices, such as providing financial compensation to Indigenous communities or including Indigenous people in organizational decision-making, the costlier measures produced significantly larger improvements in perceived social responsibility. This contrast is analytically powerful because it separates the signaling value of cheap talk from the signaling value of genuine sacrifice. Audiences, it turns out, can tell the difference between an organization that says something and one that gives something up. A land acknowledgement costs an institution almost nothing, and its reputational return is correspondingly small; compensation and shared authority cost a great deal, and their reputational return is correspondingly large.

Taken together, the findings suggest that land acknowledgements primarily serve the interests of the institutions that adopt them rather than the Indigenous communities they name. The practice improves organizational reputation at minimal cost, modestly informs audiences about Indigenous presence, but does not build support for reparative politics and may even dampen interest in Indigenous cultures. The authors characterize this as evidence that land acknowledgements generate reputational benefits rather than sociopolitical change. That conclusion does not mean the statements are meaningless, and the researchers are careful to note that awareness effects are real. But it does mean that the strongest claims made on behalf of the practice, that it builds momentum for justice, are not supported by causal evidence, and the sharpest claims of critics, that it is mere performance, receive considerable experimental backing.

The study arrives at a moment of intense contestation over symbolic politics in settler states. In Australia, the 2023 Voice to Parliament referendum demonstrated how fraught questions of Indigenous recognition have become, with the failed constitutional proposal exposing deep divisions over what recognition should entail. In the United States, land acknowledgements have spread from academic settings to professional sports, entertainment, and corporate life, drawing both praise and mockery. The new research speaks directly to this debate by showing that the symbolic and the substantive are not interchangeable: audiences reward substance more than symbolism, and symbolism alone does not move political attitudes. For Indigenous advocates, the implication may be that land acknowledgements are best treated not as ends in themselves but as openings that must be paired with demands for participation and compensation. For institutions, the message is starker: if the goal is genuine reconciliation rather than reputational management, the evidence points toward the expensive, disruptive practices that share power and resources, not the well-intentioned paragraph read at the start of the meeting.

The methodological rigor of the study strengthens these conclusions. The experiments were pre-registered in design logic, conducted on large samples across two countries, and analyzed using open-source statistical software, with all replication data and code deposited in a public Dataverse repository. The researchers also employed equivalence testing and heterogeneous treatment effect analysis to probe whether subgroups responded differently, and the consistency of results across the Australian and American contexts suggests the findings are not artifacts of a single political culture. As debates over diversity practices, corporate social responsibility, and symbolic recognition continue to intensify worldwide, this study offers a template for how such contested practices can be evaluated empirically rather than ideologically. Its central lesson is uncomfortable for everyone in the debate: words of recognition are heard, remembered briefly, and then absorbed into the routine of institutional life, while the work of justice, as Indigenous communities have long argued, happens only when resources and authority actually change hands.

Subject of Research: Experimental effects of Indigenous land acknowledgements on non-Indigenous audiences and institutional reputation in Australia and the USA

Article Title: Effects of land acknowledgements on non-Indigenous audiences in Australia and the USA

Article References: McNamee, L., & Peyton, K. (2026). Effects of land acknowledgements on non-Indigenous audiences in Australia and the USA. Nature Human Behaviour. https://doi.org/10.1038/s41562-026-02520-6

Image Credits: AI Generated

DOI: 10.1038/s41562-026-02520-6

Keywords: land acknowledgements, Indigenous recognition, reparations, collective guilt, Australia, United States, randomized experiments, corporate social responsibility, symbolic politics, institutional isomorphism, signaling theory, Nature Human Behaviour

The review, authored by Yaqi Bi, Ruijia Guo, and Xingming Fan, frames the comparison through two contrasting models. The first is an innovation-driven cycle, in which private companies are the principal engine of research and development, sustained by strong intellectual property protection and reinvested profits. The second is a public institution-centered cycle, in which government research organizations drive the core of breeding work. The distinction, the authors stress, is institutional rather than technological. Both countries now share access to the same molecular toolkit of genomic selection, high-throughput phenotyping, and programmable gene editing, which makes the stubborn performance gap all the more telling as evidence that institutions, not laboratory techniques, are doing the differentiating work.

In the American system, that machinery runs on private capital. Companies such as Corteva, which spent approximately 1.4 billion U.S. dollars on research and development in 2024, operate within a legal framework anchored by the Plant Variety Protection Act and patent law, allowing them to recoup massive breeding investments and plow returns into the next generation of hybrids. This closed loop of investment, protection, and profit has produced remarkable efficiency, particularly in selecting maize adapted to high planting densities, the cornerstone of large-scale intensive farming. But the model carries risks of its own. Strict intellectual property regimes and intense market concentration can crowd out small firms and public researchers, and the review notes that consolidation may narrow the genetic diversity of the germplasm pool, encouraging variety homogenization. The United States has historically balanced these pressures through public funding of basic research via the USDA Agricultural Research Service and the Land Grant University system, alongside policy measures aimed at promoting competition and transparency in the seed sector.

China’s system has followed a different trajectory. Breeding has long been concentrated in public institutions such as the Chinese Academy of Agricultural Sciences and provincial academies, and despite enormous government investment, the pipeline from laboratory to market has repeatedly broken down. Weak intellectual property protection historically allowed a practice the authors call imitation breeding, in which enterprises made slight modifications to existing varieties and profited at low cost. That business model gutted the incentive for genuine research investment, fragmenting the seed market into thousands of small companies with little capacity for innovation. The consequences are visible in the genetics: although thousands of new maize varieties are approved in China every year, more than 80 percent of the varieties promoted in the main production belts trace back to the backbone parental lines Zheng 58 and Chang 7-2 and their derivatives. That narrow genetic base proved dangerously fragile when southern rust swept the Huang-Huai-Hai region in 2021, causing large-scale yield losses because most promoted varieties shared a susceptible background.

The turning point came in 2021 with the launch of China’s Seed Industry Revitalization Action Plan, which explicitly designates seed companies as technological innovation entities and redirects research resources toward competitive commercial firms. Reforms such as the green channel and consortium testing have given enterprises more autonomy in variety evaluation, while approval standards have shifted from pure yield toward wide adaptability, accelerating the pace of variety upgrading. Perhaps most consequential is the 2021 amendment to the Seed Law, effective March 2022, which establishes an Essentially Derived Varieties system. Under the EDV framework, commercialized varieties modified from protected originals require the original owner’s approval, a mechanism designed to sever the profit chain of imitation breeding and push companies toward original innovation built on new germplasm and new technology. The authors caution, however, that a time lag is inevitable between policy enactment and market transformation, and that consolidating thousands of fragmented firms into globally competitive leaders will take years to materialize in measurable genetic gain.

Regulatory divergence over gene editing sharpens the contrast further. The United States, under the SECURE rule implemented in 2020, applies a product-based framework: gene-edited traits that could be achieved through conventional breeding, such as SDN-1 edits, are effectively exempt from regulatory review, enabling rapid commercial iteration of insect-resistant and herbicide-tolerant varieties. China historically regulated by process, treating the technique rather than the product as the trigger, but its 2022 guidelines for the safety evaluation of gene-edited plants introduced a tiered system for crops lacking exogenous DNA. Applicants can now proceed directly to a safety certificate after the intermediate test stage, cutting the commercialization cycle to roughly one to two years. The results followed quickly: China authorized its first safety certificate for gene-edited high-oleic-acid soybeans in 2023 and approved gene-edited maize in 2024. This positions China in the middle ground of the global regulatory landscape, between the permissive American model and the European Union’s process-based regime, which imposes full GMO-equivalent assessment and, according to the review, acts as a strong deterrent to private investment.

The quantitative indicators assembled by the authors reveal how deeply institutions shape breeding objectives, which in turn shape the crop itself. American hybrids achieved their highest documented genetic gain of 81 kilograms per hectare per year under high planting densities, reflecting decades of private investment in plant architecture suited to mechanized, intensive agriculture. Chinese varieties recorded a higher figure of 94.7 kilograms per hectare per year, but the review is emphatic that the two numbers are not directly comparable, having been drawn from different studies, periods, germplasm, and planting densities. The contrast reflects divergent breeding goals rather than superior Chinese progress: China has historically prioritized yield stability for smallholders farming scattered, variable land, while the U.S. pursues density tolerance, which delivers resilience and stable yields at equal or lower input levels. China is now raising planting densities and shifting toward intensive production, where optimizing density has been shown to lift grain yield under Chinese field conditions.

Nitrogen use efficiency tells a similar institutional story. Measured as grain produced per unit of applied nitrogen, American maize reached 49.0 kilograms per kilogram of nitrogen in 2017, nearly double the Chinese figure of 25.8. The gap, the authors argue, is not primarily technical. In the profit-driven American cycle, companies invest heavily in high-efficiency varieties because fertilizer savings translate directly into margins, and embedding nitrogen efficiency as an explicit breeding goal has improved it without sacrificing yield. In China’s output-maximizing model, fertilizer subsidies historically pushed nitrogen efficiency into a secondary role behind total production. That calculus is changing as China embraces green development, and nitrogen use efficiency has now become a key criterion in variety approval, a revision of past priorities under the government-led system. Meanwhile, R&D spending patterns are converging: China’s top seed companies have sharply increased investment, and enterprise-led innovation consortia signal a shift from a dispersed structure toward a consolidated, research-centered model.

The global implications extend well beyond the two superpowers. Brazil offers the template the review finds most instructive: after establishing the public research corporation EMBRAPA in the 1970s, the country passed plant variety protection and biosafety laws in the 1990s and early 2000s, attracting multinational firms while building local champions into an efficient public-private division of labor, with EMBRAPA supplying germplasm and pre-breeding support and private companies handling commercialization. India presents the cautionary mirror image. Despite a vast public research network under ICAR, weak intellectual property protection, a fragmented seed market, and wavering biotechnology regulation outside cotton have deterred private investment, leaving maize yields below the world average. For developing economies, the authors conclude, public funding alone is insufficient; even resource-constrained breeding programs can raise genetic gain per unit cost by optimizing scheme design, but breaking technology lock-in requires moderate government intervention paired with credible IP frameworks.

The review’s ultimate message is that neither pure market forces nor pure state planning suffices. The ideal system pairs public funding of high-risk basic research and guardianship of germplasm diversity with a competitive private sector that translates technology into farmers’ fields, the balance China is now attempting through systematic reform. And even institutional repair will not be enough on its own: converting new germplasm into faster, more predictable genetic gain will require data-driven breeding platforms that integrate genomic selection, high-throughput phenotyping, and shared databases within the smart-breeding frameworks now emerging worldwide. For a crop that underpins food security for billions, the yield gap between Beijing and Washington is ultimately a measure of institutional design, and the race to close it will be won in lawbooks and boardrooms as much as in the field.

Subject of Research: Comparative analysis of maize breeding innovation systems and their systemic drivers of breeding efficiency in China and the United States

Article Title: Systemic drivers of maize breeding efficiency in China and the U.S.

Article References: Bi, Y., Guo, R., & Fan, X. (2026). Systemic drivers of maize breeding efficiency in China and the U.S.. Journal of Agriculture and Food Research, 31, Article 103301. https://doi.org/10.1016/j.jafr.2026.103301

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103301

Keywords: maize, breeding efficiency, China, United States, intellectual property, gene editing, seed industry, genetic gain, nitrogen use efficiency, innovation systems, food security, EDV system

The research team set out to answer a deceptively simple question: who is actually represented in mobile location data, and how does that representation vary across space and demographic groups? To do so, the investigators compared the demographic and geographic composition of large-scale mobile location panels against authoritative benchmark populations drawn from the United States Census. By aligning the observed device counts with census figures across multiple spatial resolutions, from the national level down to counties and finer census geographies, the researchers were able to quantify where and for whom mobile location data over-represents or under-represents the underlying population. This benchmarking approach transforms a vague concern about bias into a measurable, mappable quantity.

The multiscale design is central to the study’s contribution. Many previous audits of mobility data focused on a single geographic level, typically the nation as a whole, where biases can average out and appear modest. But the new analysis demonstrates that national aggregates conceal dramatic local variation. A dataset that looks reasonably balanced at the country level may severely distort the picture in individual counties, particularly in rural areas, on tribal lands, and in communities with distinctive age or income profiles. Because many downstream applications, from retail site selection to emergency response planning, operate at precisely these local scales, the discrepancy between national fairness and local distortion carries real consequences.

Technically, the analysis relied on comparing device-level residence estimates with census counts of population by age, sex, race and ethnicity, income, and urbanicity. The researchers computed representation ratios, expressing the share of mobile devices attributed to a group or area relative to that group’s share of the benchmark population. Values above one indicate over-representation and values below one indicate under-representation. By computing these ratios repeatedly across scales and demographic dimensions, the team built a comprehensive portrait of sampling bias that could be decomposed into spatial components, sociodemographic components, and their interactions. This decomposition matters because spatial and demographic biases are intertwined: certain places are home to certain populations, so a geographic gap is often simultaneously a demographic one.

The findings confirm and sharpen long-standing suspicions about who is missing from mobile location data. Older adults, particularly those in the oldest age brackets, appear substantially less often than their share of the population would predict, reflecting lower smartphone adoption, different app ecosystems, and greater privacy sensitivity. Racial and ethnic minorities show uneven representation that varies by region, with some communities under-represented and others appearing at rates closer to parity. Income gradients emerge as well, with lower-income households less likely to contribute devices to commercial location panels, a pattern consistent with disparities in smartphone access, data plan affordability, and the types of applications that collect and monetize location information.

Geographically, the study finds that rural counties are systematically under-represented relative to urban cores, where dense populations, heavy app usage, and the economics of the mobile advertising ecosystem concentrate data collection. The magnitude of the rural gap is not uniform: it widens in regions with older populations and lower broadband penetration, and it narrows in peri-urban counties that blend rural character with metropolitan labor markets. The authors also document variation across states and metropolitan areas, suggesting that regional culture, state-level demographics, and the spatial distribution of technology industries all leave fingerprints on the composition of location panels. For analysts, the practical implication is that bias correction cannot rely on a single national adjustment factor.

Why do these biases arise in the first place? The study situates the problem in the mechanics of how commercial location data are produced. Devices enter these datasets only when users grant location permissions to applications that partner with data aggregators, and only when the resulting location pings pass quality filters designed to remove noise and protect privacy. Each step in this pipeline, from app adoption to permission granting to data brokerage, filters the population in ways that correlate with age, income, race, and place. The result is a dataset that is enormous, in the tens of millions of devices, yet still systematically skewed. Scale, the authors emphasize, is not the same as representativeness; a bigger biased sample is still a biased sample.

The implications ripple across the sciences that depend on mobility data. Epidemiological models that used location data to estimate contact patterns during the COVID-19 pandemic, for example, may have under-counted the movements of older and lower-income individuals, precisely the groups whose vulnerability and exposure dynamics differed most from the smartphone-owning mainstream. Transportation planners who calibrate travel demand models with mobile data risk designing infrastructure around the behavior of a demographically narrow public. Studies of segregation, access to services, and environmental exposure that infer activity spaces from location pings may mischaracterize the daily geographies of communities that are thinly sampled. The new bias maps offer these fields a diagnostic tool: before using location data for a given region or population, researchers can now check how well that region and population are actually represented.

The authors also point toward remedies. Weighting and reweighting schemes, in which devices are assigned statistical weights so that the weighted sample matches census benchmarks, can reduce aggregate bias, though the study cautions that such corrections struggle when entire groups are nearly absent from the data. Hybrid approaches that blend mobile data with traditional surveys, administrative records, or census microdata can anchor estimates to known population structure. Perhaps most importantly, the researchers advocate routine bias auditing as a standard step in any analysis using commercial location data, analogous to the data-quality checks that are customary in survey research. Transparency about representation, they argue, should become a baseline expectation for both data vendors and the scientists who consume their products.

As mobile location data continue to expand into nearly every corner of computational social science, this multiscale audit of the United States serves as both a warning and a roadmap. The warning is that the digital traces left by smartphones reflect the inequalities of digital access and technology adoption, and that these inequalities are written into the data at every geographic scale. The roadmap is a practical methodology for measuring those biases, mapping them across the country, and correcting for them where possible. In an era when decisions about public health, transportation, and resource allocation increasingly rest on algorithmic interpretations of human movement, knowing exactly who is missing from the data is the first step toward ensuring that data-driven decisions serve everyone, not just those who carry a trackable device.

Subject of Research: Spatial and sociodemographic sampling biases in mobile location data across the United States

Article Title: Characterizing the spatial and sociodemographic sampling biases found in mobile location data through a multiscale analysis of the United States

Article References: Embury, J., Dodge, S., & Nara, A. (2026). Characterizing the spatial and sociodemographic sampling biases found in mobile location data through a multiscale analysis of the United States. Scientific Reports. https://doi.org/10.1038/s41598-026-70982-9

Image Credits: AI Generated

DOI: 10.1038/s41598-026-70982-9

Keywords: mobile location data, sampling bias, human mobility, demographics, census benchmarking, spatial analysis, rural under-representation, digital divide, data representativeness, computational social science, Scientific Reports, United States

The first component of the model concerns the emergence of potential perpetrators. Using demographic data drawn from the U.S. Census, the researchers estimated a per-capita rate at which motivated individuals arise in a given population, and this rate was estimated jointly with the other model parameters rather than fixed in advance. This joint estimation is a key strength of the Bayesian approach: uncertainty in one parameter, such as perpetrator emergence, can be constrained by observations that also bear on other parameters, such as firearm availability or population structure. By allowing all parameters to be inferred simultaneously from the historical record of events, the framework avoids the pitfalls of chaining together independently derived estimates and produces a coherent probabilistic picture of shooting risk across the United States.

The second component, access to firearms, proved to be the dominant predictor of risk in the model. Because comprehensive data on private gun ownership are difficult to obtain, the researchers used the local density of Federal Firearms License (FFL) holders as a proxy for firearm availability. This proxy emerged from the calibration as the single most influential factor shaping the geographic distribution of expected shootings, outweighing the contributions of population density alone or the estimated rate of perpetrator emergence. In practical terms, the model implies that the availability of a firearm may function as an important limiting factor in mass shooting risk: where guns are more accessible, the probability that a motivated individual can translate intent into a high-fatality event rises substantially, holding other conditions constant.

The third component captures the presence of suitable target populations, reflecting the observation that mass shootings typically occur in places where potential victims gather, such as schools, workplaces, retail spaces, and public venues. By combining these three ingredients within an agent-based architecture, the simulation generates stochastic realizations of shooting risk across counties, producing not just a single point estimate but a distribution of plausible outcomes. This probabilistic character is central to the study’s forecasting ambitions. Just as epidemic models produce ranges of possible outbreak trajectories rather than deterministic predictions, the shooting model yields expected event counts and their uncertainty, allowing researchers and policymakers to reason about risk in a statistically disciplined way.

To test the model, the authors compared its predictions against mass shooting events recorded in the Mother Jones database covering 1982 through 2024. This widely used database includes approximately 160 events with three or more fatalities, excluding the perpetrator, and deliberately excludes incidents categorized as terrorism, gang-related violence, or domestic disputes. The exclusion criteria matter: they define a specific and arguably more preventable class of public mass shootings, distinct from forms of gun violence with different underlying dynamics. The researchers found that the models assigned higher risks of shootings precisely to areas where shootings had historically occurred, demonstrating that the framework can discriminate between geographic areas with genuinely different levels of risk rather than merely reproducing population counts.

Beyond retrospective validation, the calibrated model identifies the areas facing the greatest expected burden in the coming years. The ten highest-risk areas by expected events per decade are Maricopa County, Arizona; Harris County, Texas; Dallas County, Texas; Los Angeles County, California; Kings County, New York; Clark County, Nevada; Orange County, California; Queens County, New York; Cook County, Illinois; and Philadelphia County, Pennsylvania. The list spans large metropolitan counties across the Sun Belt, the coasts, and the industrial Midwest, and reflects the combined influence of substantial populations, dense networks of firearm dealers, and the urban characteristics that concentrate suitable targets. Notably, several of these counties also rank among the most populous in the nation, but the model’s ranking is not a simple population map; the dominance of FFL density as a predictor reshapes the geography of expected risk in ways that pure demographic extrapolation would not.

According to the authors, agent-based models of this kind can outperform standard statistical baselines in identifying areas at elevated risk. The improvement arises from the models’ structural realism: instead of fitting a regression to correlate inputs with outcomes, the simulation encodes a causal narrative, a motivated perpetrator meeting a firearm and a target population, and lets the data determine how strongly each element drives observed events. When the fitted mechanism reproduces historical patterns better than atheoretical alternatives, confidence grows that the model captures something real about the process, not merely a statistical coincidence. That realism also makes the framework adaptable; as new data arrive or as policy environments change, parameters can be re-inferred and projections updated within the same Bayesian machinery.

The potential applications extend to the allocation of prevention resources. If the geographic distribution of risk can be estimated with quantified uncertainty, interventions such as threat assessment programs, community-based violence prevention, extreme risk protection orders, and law enforcement preparedness could, in principle, be targeted toward the communities where expected benefits are largest. The model’s emphasis on firearm access as the dominant predictor also speaks directly to ongoing policy debates. If access to a firearm is an important limiting factor in whether mass shootings occur, then measures that reduce availability in high-risk areas, or that introduce friction into the acquisition process, may carry disproportionate preventive value relative to interventions focused solely on identifying perpetrators in advance, a task that remains notoriously difficult given the rarity and unpredictability of individual events.

The study also carries important caveats and a broader scientific significance. An agent-based model calibrated on roughly 160 events over four decades cannot predict when or where any specific attack will happen, and the use of FFL density as a proxy for gun availability introduces measurement uncertainty that the Bayesian framework represents but cannot eliminate. Mass shootings are rare, socially complex events shaped by factors, including mental health, social contagion, media dynamics, and economic conditions, that no single model fully captures. Yet the value of the work lies in demonstrating that even deeply troubling social phenomena can be brought within the reach of formal, mechanistic, data-constrained science. By combining agent-based simulation with Bayesian calibration, the researchers offer a template for rigorously reasoning about rare violent events, and a tool that, its authors argue, may help direct scarce prevention resources toward the places where they can do the most good.

Subject of Research: Bayesian agent-based modeling of the geographic risk and potential severity of mass shootings in the United States

Article Title: Forecasting mass shootings

Article References: Forecasting mass shootings. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: mass shootings, agent-based modeling, Bayesian inference, firearm availability, geographic risk, PNAS Nexus, gun violence prevention, Federal Firearms License, Mother Jones database, risk forecasting, public health, United States

The study’s scale and methodology set it apart from earlier work. Rather than treating air conditioning as a simple yes-or-no variable, the researchers constructed county-level estimates of annual average household AC usage and then examined how the relationship between daily temperature and mortality shifts across that usage gradient. County-specific temperature–mortality associations were first estimated for each county in the contiguous United States, and those estimates were then pooled through a meta-regression framework keyed to the counties’ average AC usage. This two-stage design allowed the team to move beyond correlation and characterize precisely how the shape of the temperature–mortality curve changes as cooling becomes more common in a population.

The technical results are striking in their internal consistency. When the researchers compared counties at the 10th percentile of household AC usage with counties at the median, three things happened simultaneously. First, the minimum mortality temperature—the outdoor temperature at which deaths are lowest—shifted downward, meaning that the human body’s apparent comfort zone extended toward cooler values. Second, the range of temperatures above that minimum mortality point for which mortality showed no statistically significant increase widened considerably, effectively flattening the most dangerous portion of the heat–death curve. Third, and most directly, the mortality odds ratio at the 95th percentile of temperature fell from 1.022, with a 95 percent confidence interval of 1.011 to 1.033, to 1.008, with a confidence interval of 0.999 to 1.017. In practical terms, an extremely hot day that would have raised mortality risk by roughly two percent in a low-AC county raised it by well under one percent where air conditioning use reached the median.

Perhaps the most policy-relevant discovery in the analysis, however, is what happened beyond the median. When household AC usage climbed further above that midpoint, the mortality odds ratio did not continue to fall. Instead, the benefit plateaued, indicating that the protective effect of residential cooling saturates once usage reaches roughly half of households in a county. Above that threshold, additional adoption delivers diminishing returns for population health. This plateau has profound implications for how governments think about adaptation investments: the priority is not maximizing AC penetration everywhere, but lifting the lowest-usage communities—often the hottest, poorest, and most vulnerable—toward the median, where each additional air-conditioned household buys the largest mortality reduction.

The epidemiological logic behind these findings is grounded in physiology. Extreme heat stresses the cardiovascular and respiratory systems, thickens blood, impairs thermoregulation, and disproportionately kills elderly people, people with chronic disease, and those without access to cooled environments. Indoor cooling interrupts this cascade by lowering core body temperature and reducing the physiological strain of hot nights, which are increasingly recognized as a key driver of heat deaths. Earlier research, including a landmark study of the twentieth-century decline in the US temperature–mortality relationship published in the Journal of Political Economy, had pointed to air conditioning as the leading explanation for Americans’ growing resilience to heat. The new study quantifies that resilience county by county, on modern data, and with the statistical machinery needed to separate AC’s effect from other influences such as demographics, healthcare access, and long-term acclimatization.

To build their AC usage estimates, the team relied on a fine-scale dataset of multidimensional household well-being developed by co-authors Narasimha D. Rao and Karthik Akkiraju and collaborators, published in Scientific Data in 2024, which fuses multiple household surveys to produce spatially detailed portraits of American living conditions. Mortality data came from the National Center for Health Statistics Research Data Center of the US Centers for Disease Control and Prevention, while daily gridded weather data were drawn from the PRISM climate database at Oregon State University and population exposures from the LandScan Global one-kilometer population grid. The researchers also conducted an extensive battery of sensitivity analyses—varying temperature time windows, spline specifications, adjustment for fine particulate matter pollution, and restricting the analysis to summer months—finding that the core results held across all of them.

The maps of averted mortality that emerge from the analysis tell a story of deep geographic inequity. The largest avoided death burdens concentrate where the dual conditions of high heat exposure and widespread residential cooling coincide, while counties in the Southeast, Southwest, and parts of the Midwest show the biggest absolute benefits. Conversely, regions where heat risk is rising but AC adoption lags—often because of poverty, aging housing stock, or energy insecurity—stand out as areas of unmet need. The study’s authors note that in 2020, 27 percent of US households reported difficulty meeting their energy needs, according to the US Energy Information Administration, a reminder that the cooling that saves lives is itself unevenly affordable. Energy burden, in this framing, is a direct mortality risk factor.

Yet the paper is careful not to present air conditioning as an unqualified good. The authors explicitly underscore the need for strategies that balance the survival benefits of AC against the harms of overuse, which include surging electricity demand on the hottest days, greenhouse gas emissions from fossil-fueled generation, waste heat vented into urban streets, and the refrigerant emissions that potentiate further warming. The plateau finding sharpens this calculus: because health benefits saturate near median usage, the marginal emissions cost of pushing adoption far beyond that level yields little additional protective return. The rational adaptation portfolio, therefore, pairs targeted expansion of cooling access for vulnerable and low-usage populations with efficiency standards, grid decarbonization, passive cooling design, urban shade and reflective surfaces, and community interventions such as cooling centers, whose public health effectiveness has been reviewed in the European Journal of Public Health.

The stakes of getting this balance right will only grow. The Lancet Countdown’s 2024 report documented record-breaking climate-related health threats, and studies of population aging project that temperature-related mortality will rise substantially at higher levels of global warming even under optimistic scenarios. The research team’s companion work, published in JAMA Network Open in 2025, estimated the heat and cold mortality burden in the US from 2000 to 2020, providing the baseline against which the new averted-death figures are measured. Together, these findings reframe household air conditioning from a comfort appliance into critical health infrastructure—whose reach, affordability, and carbon footprint will help determine how many people the coming decades of heat will claim. As climate change pushes temperatures past thresholds the human body cannot tolerate, the authors conclude, ensuring equitable access to safe indoor cooling while managing its energy costs stands as one of the defining adaptation challenges of the century.

Subject of Research: The effect of household air conditioning usage on heat-related mortality across the contiguous United States

Article Title: Impact of household air conditioning usage on heat-related mortality in the USA

Article References: Chu, L., Akkiraju, K., Rao, N. D., Dubrow, R., & Chen, K. (2026). Impact of household air conditioning usage on heat-related mortality in the USA. Nature Health. https://doi.org/10.1038/s44360-026-00184-0

Image Credits: AI Generated

DOI: 10.1038/s44360-026-00184-0

Keywords: air conditioning, heat-related mortality, climate adaptation, public health, temperature–mortality association, heat waves, energy insecurity, meta-regression, epidemiology, United States, climate change, mortality burden

The study, led by environmental epidemiologist Amruta Nori-Sarma of Harvard T.H. Chan School of Public Health in collaboration with colleagues at Truveta, Harvard, and Boston University, exploited a technological capability that earlier generations of heat researchers lacked: continuously refreshed electronic health record data. Rather than waiting months for claims data to be processed and aggregated, the team drew on state-day counts of emergency department visits from 19 eastern states, allowing them to quantify the health burden of the summer 2025 heatwaves while the season was still underway. In total, the analysis encompassed 8,169,637 emergency department visits recorded during the warm seasons of 2023 through 2025, providing a robust historical baseline against which the 2025 episodes could be compared.

The two heatwaves under scrutiny were stark in their timing and severity. The first gripped the region from 22 to 25 June 2025, and the second returned from 10 to 13 August 2025, engulfing the eastern United States in conditions that triggered National Weather Service heat alerts across much of the study area. To estimate how many visits these episodes caused, the researchers compared observed visit counts during the heatwave windows with counterfactual predictions of what visits would have been under typical temperature conditions, using temperature-health associations estimated from the prior three warm seasons.

Technically, the analysis rested on a conditional Poisson model, a statistical framework well suited to time-series data on disease counts. The researchers stratified time by year, calendar month, and day of week, with stratum-specific fixed effects that absorb routine patterns in healthcare utilization, such as weekday and seasonal variation. This design effectively compares hot days with cooler days occurring under otherwise similar conditions, a strategy closely related to the time-stratified case-crossover approach widely used in environmental epidemiology. Temperature exposure was modeled using distributed lag non-linear models, or DLNMs, which capture two crucial features of heat’s health effects simultaneously: the non-linear dose-response relationship between temperature and risk, and the fact that effects unfold over multiple days, with heat stress on one day influencing emergency visits over a window of zero to four days afterward.

The headline numbers were striking. During the June 2025 heatwave, the researchers estimated that 9.2 percent of all-cause emergency department visits were attributable to heat over the zero-to-four-day lag window, with a 95 percent confidence interval of 6.2 to 11.6 percent. During the August heatwave, the attributable fraction was 8.3 percent, with a confidence interval of 6.0 to 10.1 percent. In plain terms, roughly one in every eleven or twelve people who walked into an emergency department in these nineteen states during those weeks was there, at least in part, because of extreme heat. Similar patterns emerged when the team examined cumulative lags and cause-specific outcomes, indicating that the association was not an artifact of a single modeling choice.

Because the underlying data included diagnostic information, the researchers could decompose the burden by cause. Beyond direct heat-related illness diagnoses, they tracked emergency visits for kidney disease and for mental health conditions, both of which have well-documented physiological links to heat exposure. Kidney disease is acutely sensitive to dehydration and thermal strain, while a growing body of literature connects high ambient temperatures to psychiatric crises, including exacerbations of mood disorders and substance-related emergencies. The lag-specific analyses showed that the association between the 99th percentile of daily maximum temperature, about 36.9 degrees Celsius, and the sample median of 27 degrees Celsius was strongest on the same day for direct heat illness, while kidney and mental health outcomes followed somewhat different lag structures, consistent with the diverse physiological pathways through which heat injures the human body.

Those pathways are worth spelling out. Extreme heat forces the cardiovascular system to work harder, shunting blood toward the skin to dissipate warmth and increasing cardiac output, changes that laboratory studies involving more than 400 controlled heat exposure experiments have documented in detail. In people with preexisting heart disease, this added strain can precipitate decompensation. Dehydration concentrates the blood and promotes the formation of kidney stones and acute kidney injury, particularly in older adults and in people taking common medications that impair thermoregulation or fluid balance. Meanwhile, heat disrupts sleep, alters neurotransmitter function, and can increase impulsivity and aggression, mechanisms that plausibly underlie the observed rise in mental health emergency visits during hot weather.

The heterogeneity analyses added an important dimension to the findings. By fitting subgroup models for six age groups, three US census regions, and both sexes, the researchers probed whether the temperature-emergency visit association varied across populations. The results, visualized in forest plots comparing rate ratios at lag zero, showed differences by age, region, and sex, echoing decades of evidence that the very young, older adults, and residents of areas unaccustomed to extreme heat bear disproportionate risk. The state-specific exposure-response functions also revealed geographic variation: states with historically milder summers tended to show steeper increases in emergency visits per degree of warming, a pattern consistent with the idea that populations adapt, physiologically and infrastructurally, to the temperatures they usually experience, and that anomalous heat is most damaging where it is least familiar.

Methodological sensitivity checks strengthened the study’s credibility. The team replicated the primary analysis using daily average temperature instead of daily maximum temperature, and separately extended the lag window from four to seven days; both variations reproduced the central findings. Exposure data were drawn from the Open-Meteo weather API and National Weather Service records, and heat alert dates by state were compiled from National Weather Service advisories, allowing the investigators to anchor their heatwave definitions in the same official warnings that reached the public during those weeks. All analytic code, including the data extraction scripts, DLNM fitting routines, meta-analysis, and attributable burden estimation, has been made publicly available on GitHub, an unusual and welcome degree of transparency for a rapidly produced surveillance analysis.

The broader significance of the study lies less in any single percentage than in what it demonstrates about the future of climate-health surveillance. Traditional epidemiology delivers its verdicts long after the disaster has passed, when the findings can inform the next heat season but not the current one. By contrast, a near-real-time pipeline built on continuously refreshed electronic health records can tell public health officials, while a heatwave is still unfolding, how many excess patients are arriving, which conditions are driving the surge, and where resources are most strained. The authors argue that this capability should become a standing component of heat preparedness, complementing heat action plans and warning systems whose effectiveness, demonstrated in cities from Philadelphia to Montreal, depends on knowing when and where the danger peaks. As climate change renders summers like 2025 more frequent and more intense, the study suggests that the emergency department itself, properly instrumented, can serve as an early-warning sensor for the health impacts of a warming world, and that the true toll of extreme heat is far larger than the narrow category of heatstroke diagnoses would suggest. Nearly a tenth of all emergency care during those scorching weeks was heat’s shadow, and counting it in real time may be the first step toward preventing it.

Subject of Research: Attribution of summer 2025 US heatwave emergency department visits using electronic health records

Article Title: Impact of the summer 2025 heatwaves on emergency department visits in the USA

Article References: Nori-Sarma, A., Cartwright, B. M., Zanobetti, A., Pastwa, A., Stucky, N., & Willis, M. D. (2026). Impact of the summer 2025 heatwaves on emergency department visits in the USA. Nature Health. https://doi.org/10.1038/s44360-026-00194-y

Image Credits: AI Generated

DOI: 10.1038/s44360-026-00194-y

Keywords: heatwaves, emergency department visits, electronic health records, extreme heat, public health surveillance, climate change, epidemiology, distributed lag non-linear models, heat-related illness, kidney disease, mental health, United States