Science As a Battlefield

Science As a Battlefield: Knowledge, Capital Accumulation and Class Struggle

By Diego Kozlowski, Natsumi S. Shokida, Carolina Pradier

Volume 27, no. 2, Political Economy of Science

S Foster Dimini
Art by S Foster Dimini

 

We were taught that science is a global enterprise for the benefit of humanity. Nevertheless, we are often confronted with the evidence that science is used for war and oppression. What determines whose interests science serves?

Marx offers a valuable method for understanding the role of science in society. Since the time of his writing, the centrality of science has grown exponentially. This is evident in the expansion of scientific output across articles, journals, or PhD graduates, in what de Solla Price called the Big Science of the 20th century.1 With this developed form of science, new opportunities for a deeper understanding of its role in society emerge. Although several attempts were made by Marxist scholars to develop the role of science in society, we believe there is much more to be done. In this piece, we understand science as a requirement for capital accumulation, on one hand as a productive force embodying the general intellect—a concept that Marx takes from William Thompson that refers to the general social knowledge in society—through which the production of relative surplus value is enabled, and on the other hand, as an apparatus of ideological production.2

Capitalism Needs Science

This article is anchored in Marx’s most important work, Capital, and the concept of relative surplus value.3 Simple surplus value is the difference between what the individual capitalist pays their workers and the value those workers produce for them. Following Marx, the payment to those workers is the amount of value needed to reproduce their lives normally. Capitalists are driven by their interest in maximizing their profit, and one way to achieve this is through technological changes that make their factories more productive than those of their competitors. In this way they can extract more value from their workers—but when those technical changes become the new norm, the extraordinary profits vanish, and capitalists are faced with the renewed need to develop technical changes. In this continuous process, as this technical race is extended through all branches of production, it also affects products that determine the value of the labor force—the products consumed by the workers for their own reproduction—reducing the cost of the labor force and accelerating the capital accumulation process. Marx calls this emergent phenomenon relative surplus value.

The capitalist system is not driven by the will of any individual capitalist, but by an overarching logic that follows the maximization of relative surplus value, even if this process is unknown to capitalists who only care about maximizing their profit through competition. Within this dynamic, science plays a central role as it generates the knowledge needed for technical changes. It is not simply a tool at the service of individual capitals, but an enabler of the global process of capital accumulation. In this work, we will use this framework to understand science as part of the capitalist accumulation process.

Nevertheless, when Marx was writing in the nineteenth century, science was different from what it is today, and Marx’s analysis of science was very preliminary. His most developed attempt to understand the role of scientific knowledge was the concept of general intellect in the Grundisse, where he states that “…general social knowledge has become a direct force of production….”4 According to our understanding, the general intellect comprises three components: 1) practical knowledge, which is intrinsically linked to the working experience itself and therefore cannot take a completely autonomous form; 2) scientific knowledge, which takes the form of a specific branch of production, an idea later developed by Rose and Rose; and 3) technological developments, which constitute the objectification—materializing intellectual knowledge into tangible forms—of knowledge into means of production.5 Given these three components, understanding the role of science in society requires understanding its relationship and boundaries  with technology.

Two Capitalist Forms of Knowledge

Science and technology distinctly contribute to knowledge production. Traditionally, science has been understood as the primary sphere of knowledge production, while technology represents the crystallization of that knowledge into machinery. Yet, we observe that both spheres involve processes of knowledge production and objectification. From our perspective, science focuses on more abstract forms of knowledge, whereas technology leans towards knowledge with direct applications, particularly those that enhance productivity of labor. Both science and technology operate through specific institutional frameworks and dynamics. The material differences in their production processes set them apart as distinct stages in the generation of relative surplus value, while also creating formal differences in the organization and circulation of labor.

A possible way to trace their differences is by analyzing how they solve two tensions associated with knowledge production: 1) redundancy versus novelty, and 2) risk versus reward. Scientific consensus emerges through overlapping research—multiple investigations on the same topic, approached from different perspectives, that converge on similar conclusions. Crucially, each contribution must contain an element of novelty. To avoid redundancy—repetition without any contribution—previous findings must circulate freely among scientists. Scientific knowledge is therefore materialized in scholarly communication such as books, articles, or conference proceedings, so that other scientists can use it as their starting point. From this perspective, the Open Access movement can be read as an expression of the broader needs of capital accumulation, in opposition to the interests of specific private capitals that profit from restricting scholarly communication in detriment to the scientific enterprise.

By contrast, the private character of technological knowledge is essential to securing superprofits. That is, to secure comparative advantages from such applications, this knowledge must remain privately owned. Technology crystallizes knowledge into actionable tools—machinery, software, or procedures—while simultaneously creating barriers to restrict access by competitors. Patents and industrial secrets are key mechanisms of this enclosure.

The second differential aspect between science and technology is how they manage the risk versus reward trade-off. The more foundational the research, the more distant it is from immediate application, and the greater the likelihood that it will not result in a concrete use. Nevertheless, this distance also implies the possibility of multiple different applications. Basic research thus carries both higher risks and potentially higher rewards. These rewards, associated with diverse applications, are more difficult for any individual capital to appropriate.

General knowledge provides the foundation for applied knowledge. For this reason, the development of basic knowledge is a necessary precondition for all capitals to pursue specific innovations. Since most individual capitals lack the capacity to undertake this task on their own, the expansion of basic knowledge is often taken by the state(s), acting as the representative of capital in general. By contrast, individual capitals typically focus on applied knowledge with direct uses.

From Machinery to Health, Science Contributes to Capitalist Accumulation

Traditionally, Marxist analysis of science focused exclusively on the increases of productivity objectified in machinery.6 But production is more than machines, and science is more than engineering.7 If we see the distribution among disciplines in modern science, we can observe the prominent role of life sciences and social sciences in tandem with physical sciences and engineering.

The better understanding of natural forces applied to the increase in productivity with a focus on the production of machinery and automation draws on the knowledge produced by numerous scientific disciplines. For instance, the petrochemistry industry is highly dependent on materials science, which integrates principles from chemistry, physics, and ultimately mathematics. Other fields like computer science have direct application in multiple branches of production.

The social organization of work also has a direct implication in productivity. Areas of study such as industrial organization, management, logistics, or human resources studies focus on how a better organization of the human-centered working processes can increase the productivity of the collective worker. From micro-level aspects such as the optimization of labor division in a factory to the coordination of a global value chain, the increasing complexity of work processes requires a scientific understanding for its management. The minimization of times of storage and circulation of goods, as well as the best organizational structures for different types of firms, among others, are all scientific developments that directly affect the productivity of labor without directly being objectified in machinery.8

Capitalism needs to guarantee the existence of a labor force with physical and mental conditions suitable for its exploitation. The state that represents the interest of the individual capitals within its geographical boundaries directly or indirectly provides health, education, and social services, creating economies of scale for the production and sustainability of workers’ lives. Multiple disciplines are specifically oriented toward this goal, and the knowledge they produce can improve the productivity and efficiency of the state in its mission. The field of education develops the best way to produce the productive subjectivity needed for the labor market, while medicine and health focus on the physical and psychological conditions. Even for those countries where parts of health and educational services are privatized (e.g., the US), the state is still the largest funder of research related to those fields.

The Role of Ideology

In capitalism, our subjectivity is produced by and for the system, in what Marx called the real subsumption of labor under capital.9 The rapid changes in production introduced by new technologies also imply changes in the workers’ productive subjectivity. These changes not only include a transformation of workers’ technical skills but also involve our conception of society—why and how society is how it is—including its ideological basis. The development of a scientific consciousness implies, for example, the need for a scientific justification of the political system. If we are taught to have a scientific understanding of the natural forces, other ideological tools such as religion lose persuasion power. Therefore, science is also called to produce the ideological framework that is needed in different contexts, providing theory and empirical evidence. Within this framework we understand that social sciences and humanities provide a field for political disputes, introducing a common language among political contenders. This reflects the limits of what can be reasonably argued relying on scientific discourse. This idea previously appeared in the 1970s, when science was seen by some as a tool for social control through the development of means of repression (e.g. war machinery or surveillance software) and the manipulation and control of the population through ideology.10 More recently, economics was highlighted as the discipline for the justification of austerity plans, while Berardi defines economics as the ideological technology designed to subsume engineers under the dispositions of the capital. From our perspective, these conceptions of ideology are limited, as social sciences can also play a crucial role in the development of critical and revolutionary subjectivities.11

Social science produces a regulatory ideological frame of the political field in three ways: first, it creates an explanation, or many, of how society works and why. Second, it creates concrete outputs in the form of policy recommendations and scientific articles with explicit policy implications. Third, through higher education, professors reproduce their worldviews into the next generations. This scientific production shapes the space of possibility of science-based recommendations that policymakers can use to justify their decisions. Academic freedom is essential to create a wide enough spectrum of options for policymakers to choose from as they consider convenient. Scientific consensus can only partially limit this discretional use of science for policy justification, as social sciences’ consensus are partial and related to schools of thought. Social sciences can therefore play an apologetical role. On the other hand, social sciences can also be used critically as a tool for social change. Social movements can also frame their critical stand on non-mainstream scientific publications, and on heterodox scientific consensus, that are extended among social scientists.12 Even more, some research areas are almost exclusively and explicitly critical: black studies, gender studies, decolonial studies, social ecology, among others, are aligned with specific political agendas of the working class. Academic freedom has the central role of creating both opposing conclusions and a common language to organize the political dispute. Of course, the political dispute can derail from the boundaries that the evidence-based discussion allows, and extreme-right governments frequently invoke nonscientific justifications, based on religion, chauvinism, or even conspiracy theories. From this perspective, we can understand that using Kuhn’s framework to consider social sciences as pre-paradigmatic or pre-scientific is problematic because the lack of consensus is a need for the capital accumulation process that drives science.13

Within this framework, natural and life sciences are not exempt from ideological and political disputes. For instance, in biology and biomedicine, the treatment of sex as a fixed, binary variable has historically played a central role in legitimizing gender differences in society. Informed by the feminist movements, alternatives to the binary and essentialist approaches had also emerged within these disciplines to recognize the pluralism and context-specificity of operationalizations of “sex” across experimental research.14 Similarly, genomics shape broader social understandings of human difference. Eugenics is the tragic example of how research on genetics can reinforce racist ideologies that end up fueling fascist governments and their anti-immigration and forced sterilization campaigns.15 Nowadays, many scientists and research communities continue working to dismantle eugenic myths, while accounting for their impact on people of color, people with disabilities, the LGBTIQ+ community, and others.16

From this perspective, science is a form of class struggle and will therefore be affected by the shifts in the power imbalance that correspond to a specific historical context. Critical or apologetical stands do not have the same traction in the political arena, nor in academia. While science provides an intellectual framework for the political battlefield, the outcome of those political disputes also have repercussions on what research outputs are produced. We observe two mechanisms that determine what type of ideology science can produce. First, the material resources that governments assign to specific research lines are in direct relation with the power imbalance between specific interests in dispute. For example, the new Trump administration has imposed radical changes on US funding, with an explicit agenda in mind and lists of research subjects censored from public funding.17 Second, the dominant ideology in any specific historical context will also affect the ideological stance of scientists themselves—and even who gets to be a scientist—reflecting their personal interests into their work.18 What we consider a relevant object of study, and how we approach it, is affected by our contexts. Even more, material historical context and ideological forms shape what a scientific community considers valuable research, affecting publications and impact. Consequently, we find a reciprocal relation where science frames the political discussion, and the political context influences science directly through the institutional promotion—or censoring—of certain discussions, and indirectly through the standpoint of each scientist both when choosing their research topic and when facing their object of study.19

Our Place in the Battlefield

Capitalism needs science. This implies that the scientific worker has a privileged position in class struggle. From our perspective, the determinations that condition scientists’s work are not only an expression of lack of freedom. On the contrary, as Engels says in the Anti-Dühring, Freedom is the recognition of necessity.20 Understanding the role we play improves our capacity to act on it.

All scientists, as members of the working class, need to be called to action.21 We have an active and privileged role to play, pushing scientific agendas toward the common good, and not at the service of a handful of private capitals. We need science that advocates for inclusive health, not science at the disposition of pharmaceutical companies. We need science for social justice, not science that permanently justifies austerity measures. We need an emancipatory science that improves living conditions, and not a science for war. In a context of rising international disputes, we need to highlight the collaborative and global nature of science and actively boycott scientific developments that go against humanity. And we need to apply this same logic to think about science itself. We need a critical understanding of the role of science in society to help us in this dispute.

Acknowledgements

The authors want to thank Fernando Cazón, Martin Ferroni, and Mariana Mendonça for their collaboration on prior versions of this project. We also want to thank Pierre Benz and Lucia Céspedes for their useful comments and suggestions.

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Diego Kozlowski is a postdoctoral researcher at the University of Montreal. He studied Economics and Data Science at the University of Buenos Aires and earned his PhD from the University of Luxembourg. His research explores the dynamics of scientific production and global inequalities in science. He uses bibliometrics, text mining, and network analysis to map knowledge production and contributes to equity, diversity, and inclusion (EDI) policy research. Natsumi S. Shokida is a PhD candidate at the École de bibliothéconomie et des sciences de l’information, Université de Montréal. Her research focuses on the bibliometric analysis of Gender Studies. She holds a Licenciatura in Economics from the University of Buenos Aires and a master’s in Information and Computer Science from the University of Luxembourg. She is also a member of EcoFeminita, an Argentine feminist civil society organization. Carolina Pradier is a PhD candidate in Information Science at the University of Montreal. Her academic background includes a degree in Economics and a Master’s in Labour Studies from the University of Buenos Aires. Currently, her research combines bibliometric analysis and natural language processing techniques to study the mechanisms structuring gender inequalities in science in Latin America.

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Notes

  1. Derek John de Solla Price, Little Science, Big Science (Columbia University Press New York, 1963).
  2. Matteo Pasquinelli, The Eye of the Master: A Social History of Artificial Intelligence (New York: Verso, 2023); William Thompson, An Inquiry Into the Principles of the Distribution of Wealth Most Conducive to Human Happiness: Applied to the Newly Proposed System of Voluntary Equality of Wealth, (Longsman, Hurst, Ross, Orme, Brown and Green, 1824).
  3. Karl Marx, Capital: A Critique of Political Economy, Vol. 1 (CreateSpace Independent Publishing Platform, 2010).
  4. Karl Marx, Grundrisse: Foundations of the Critique of Political Economy, 1973rd ed. (Penguin Books, 1973), 706.
  5. Hilary Rose and Steven Rose, “The Incorporation of Science,” in The Political Economy of Science: Ideology of/in the Natural Sciences (London: Macmillan Education UK, 1976), 14-31.
  6. JD Bernal, The Social Function of Science (London: Faber, 2010); Henryk Grossmann, “The Social Foundations of the Mechanistic Philosophy and Manufacture,” in The Social and Economic Roots of the Scientific Revolution: Texts by Boris Hessen and Henryk Grossmann, (Dordrecht: Springer Netherlands, 2009), 103–156; Boris Hessen, “The Social and Economic Roots of Newton’s Principia,” in The Social and Economic Roots of the Scientific Revolution: Texts by Boris Hessen and Henryk Grossmann (Dordrecht: Springer Netherlands, 2009) 41-101.
  7. We include in our definition of science the whole scientific enterprise, understood as a branch of production, and beyond epistemological considerations (e.g. math and philosophy are part of science).
  8. Benjamin Coriat, Science, Technique et Capital (SEUIL, 1976); Frederick Winslow Taylor, The Principles of Scientific Management, with Prelinger Library (New York, London, Harper & Brothers, 1911), http://archive.org/details/principlesofscie00taylrich; Gary Gereffi et al., “The Governance of Global Value Chains,” Review of International Political Economy 12, no. 1 (2005): 78–104; T. C. Cheng and S. Podolsky, Just-in-Time Manufacturing: An Introduction (Springer Science & Business Media, 1996).
  9. Marx, Capital.
  10. Rose and Rose, “The Incorporation of Science.”
  11. Clara E. Mattei, The Capital Order: How Economists Invented Austerity and Paved the Way to Fascism (University of Chicago Press, 2022); Franco Berardi, Futurability  (Verso, 2019); Guido Starosta, Marx’s Capital, Method and Revolutionary Subjectivity (Haymarket Books, 2017).
  12. Pierre Bourdieu et al., Interventions, 1961-2001: Science Sociale et Action Politique, 1st edition (Agone, 2002); Laurence Cox, “Movements Making Knowledge: A New Wave of Inspiration for Sociology?,” Sociology 48, no. 5 (2014): 954–71, ; Geoffrey M. Hodgson, “Debating the Future of Heterodox Economics,” Journal of Economic Issues 55, no. 3 (2021): 603–14; Andrew Mearman et al., “What Is Heterodox Economics? Insights from Interviews with Leading Thinkers,” Journal of Economic Issues 57, no. 4 (2023): 1119–41.
  13. Lee Harvey, “The Use and Abuse of Kuhnian Paradigms in the Sociology of Knowledge,” Sociology 16, no. 1 (1982): 85–101.
  14. Sarah S. Richardson, “Sex Contextualism,” Philosophy, Theory, and Practice in Biology 14, no. 0 (2022).
  15. Catherine Bliss, Social by Nature: The Promise and Peril of Sociogenomics (Stanford University Press, 2018).
  16. Kyle B. Brothers et al., “Taking an Antiracist Posture in Scientific Publications in Human Genetics and Genomics,” Genetics in Medicine 23, no. 6 (2021): 1004–7.
  17. Natsumi Shokida et al., “Keyword Newspeak: Trump’s Orwellian Censorship of DEI in Science,” preprint, OSF, April 19, 2025.
  18. D. Kozlowski et al., “Intersectional Inequalities in Science,” Proceedings of the National Academy of Sciences of the United States of America 119, no. 2 (2022): e2113067119.
  19. Sandra Harding, Whose Science? Whose Knowledge? (Cornell University Press, 2016).
  20. Friedrich Engels, Anti-Dühring (Wellred, 2017), 130.
  21. While we consider all scientists to be part of the working class, there are indubitable differences in terms of hierarchy and power imbalances that rule the relations among scientists. We believe that the framework outlined in this article is an important starting point to understand those inequalities as part of science’s role in capital accumulation.