Editorial: Special issue on “In what sense can the humanities and social sciences become sciences distinct from and independent of the natural sciences?”

Imagining a Place for Sustainability Management: An Early Career Call for Action

Social Science and Its Frontiers Myron P. Gutmann (bio) Mark Solovey,Social Science for What? Battles over Public Funding for the “Other Sciences” at the National Science Foundation. Cambridge, Massachusetts: MIT Press, 2020. X+ 398pp. Figures, notes, index. $50.00. Americans often date the emergence of a strong commitment to government support of science to the launch of the Soviet Union’s Sputnik 1 satellite in October 1957. That event certainly spurred policy decisions that increased federal investments in education and science, and thus is an appropriate starting point for the popular narrative about science. At the same time, policy developments of the Sputnik era built on earlier events, widely recognized by historians of science. That perspective starts the story with the presentation in July 1946 of Vannever Bush’s report, Science, The Endless Frontier, to President Truman, advocating for a large, organized federal investment in scientific research, based on the role of science and technology in the Second World War. Early efforts to enact legislation based on the Bush report failed (Truman vetoed the first bill that passed because it lacked presidential control over the appointment of the Foundation’s leadership), but in 1950 Truman signed the National Science Foundation Act, establishing an enduring basis for publicly—especially federally—funded scientific research in the United States. The debates about the creation of the National Science Foundation pitted progressives against conservatives and advocates of public and congressional control of science against advocates of exclusive control by scientists.1 One of the topics of debate—although hardly the loudest—was whether the social sciences would be included in the Foundation’s charge.2 Vannever Bush was opposed to their inclusion, sometimes arguing that they should be supported by a separate organization; on the other side, Democratic West Virginia Senator Harley M. Kilgore, a leading sponsor of a more progressive approach, supported their inclusion in the Foundation’s mission. In the end, the compromise legislation that Truman signed in 1950 did not include support for the social sciences, but at the same time did not prohibit such support. The Foundation did not totally exclude the social sciences for long; it hired sociologist Harry Alpert in 1953, and in 1954 introduced a first, extremely modest, program to support the linkage between the social and natural sciences. [End Page 396] The first Social Sciences Division was not established until 1960 (in an era in which the Foundation was divided into four scientific divisions reflecting major disciplinary categories). Later, when the Foundation was reorganized into seven directorates (three of them disciplinary, one for education, and three for administrative activities) in 1975, the Divisions of Social Sciences and Behavioral and Neural Sciences were part of an expanded Directorate for Biological, Behavioral and Social Sciences (p. 179). Only in 1991–92 did the Foundation establish a separate Directorate for the Social, Behavioral and Economic (SBE) Sciences, an organizational status that still exists today. The road from the origin of the Foundation to the creation of the SBE Directorate was not linear, with ups and downs in support for the social and behavioral sciences mostly reflecting political and institutional challenges. This history spanning the period from the first discussions of the National Science Foundation through the end of the 1980s (with an added discussion of recent events and recommendations for the future) is the topic of Mark Solovey’s Social Science for What? Battles over Public Funding for the “Other Sciences” at the National Science Foundation. In this book he builds on his earlier book, Shaky Foundations: The Politics-Patronage-Social Science Nexus in Cold War America (2013), on extensive archival research, and on interviews with surviving participants. Social Science for What? is an impressive accomplishment, capturing the connections between partisan politics, scientific inquiry, tensions among scientific disciplines, and the institutional development of the Foundation. It is instructive for all readers, including for me, who served for four years (2009–13) as one of the Foundation’s Assistant Directors and head of the Directorate for Social Behavioral and Economic Sciences (SBE). Social Science for What? articulates consistent themes that define social science at NSF, along with a lively narrative arc. To define that arc, Solovey divides the main...

The integration of natural and social sciences has been recognized as a key aspect of Earth System (E.S.) research, a cross-disciplinary field involving the study of the geosphere, the biosphere, and society (IGBP, 2006; Leemans et al., 2009; Pfeiffer, 2008; Reid et al., 2010; Young, 2008). Because of societal and political correlates between environmental change and socio-economic development, the study of the Earth System has been increasingly ascribed social and political dimensions emphasizing the need for greater collaboration between the social and natural sciences (Beven, 2011; Kates et al., 2001; Leemans et al., 2009; Reid et al., 2010; Saloranta, 2001; Shackley et al., 1998). The problem of inter-disciplinary articulation between the social and natural sciences is not specific to E.S. research, and its challenges can be traced back to the very origins of the notions of science and social science (e.g. Comte, 1830-1842; de Alvarenga et al., 2011; Latour, 2000, 2004). To a degree, these challenges could be explained in terms of the increasing gulf between two cultures – those of the sciences and the humanities – as suggested by C.P. Snow (1905-1980) in an instigating essay (Snow, 1990 [1959]), due to the high specialization in science and education, and, not less important, to a “tendency to let our social forms to crystallise” (Snow, 1990: 172). More to the point, the increasing importance attributed to the problem has motivated a growing number of analyses concerning the high level of specialization and fragmentation of science and university education (e.g. de Alvarenga et al., 2011; Moraes, 2005; Snow, 1990), but also the societal and political questions concerning research agendas (e.g. Alves, 2008; Kates et al., 2001; Latour, 2000, 2004; Schor, 2008), the disparities between developed and developing countries not just in affluence level, but also in research capacity (Kates et al, 2001; Pfeiffer, 2008; Schor, 2008), and, finally, from a more methodological point of view, the multiplicity of theoreticomethodological perspectives admitted by the social sciences (e.g. de Alvarenga et al., 2011; Floriani et al, 2011; Giddens, 2001; Leis, 2011; Moraes, 2005; Oliveira Filho, 1976; Raynaut & Zanoni, 2011; Weffort, 2006). Yet, in the E.S. field the problem of bringing together social and natural sciences has been a permanent and still unresolved challenge (Alves et al., 2007; Alves, 2008; Geoghegan et al.,

Background. Literature indicates that in academic writing, authors are expected to demonstrate a noticeable stance so that they can make their meaning clear. Therefore, differences between native and non-native writers along with cross-disciplinary academic writing assume great significance. Purpose. The interactional, dialogic, and reflective nature of academic writing requires writers to utilize stance-establishing tools in their writing, the most prominent ones being stance nouns. In addition, the that-clause construction plays a vital role in conveying the author’s stance. Studies that compare L1 Turkish writers of English and L1 English writers regarding academic writing are rather scarce. As such, the present paper aims to analyze L1 Turkish writers of English and L1 English writers in eight disciplines from natural and social sciences in terms of the use of stance nouns in that-clause constructions. Methods. The study employs Jiang and Hyland's (2016) functional classification model in exploring the nominal stance in cross-disciplinary writing of L1 Turkish writers of English and L1 English writers. To this end, journals with high impact in eight disciplines from social and natural sciences were scanned and a total of 320 articles were included in the corpus. The social sciences included in the present study cover applied linguistics, history, psychology, and sociology while the natural sciences cover medicine, engineering, astronomy, and biology. In total, a corpus of 2.232.164 words was formed. Results and Implications. The study found significant differences not only in terms of natural and social sciences but also in terms of L1/L2 distinction. In addition, a secondary purpose of the study was to see whether writers in social and natural sciences differed in terms of empiricist and interpretive rationality. The results indicated that writers in social sciences tended to use more status and cognition nouns, indicating that they tend to be more interpretive. With significant differences between Turkish and English writers from a cross-disciplinary perspective, the present study offers important insights into how writers weave their stance in academic writing. Moreover, the present study also confirmed that writers in social sciences, whether L1 or L2, tend to use more stance nouns compared with writers in natural sciences.

Arien Mack Editor’s Introduction WHEN I FIRST BEGAN TO DISCUSS THE THEME OF “ERRORS” WITH MY coeditor for this special issue, Gerald Holton, the question arose as to whether the kinds of “fruitful” mistakes that occur in the natural sciences also occur in the social sciences. While the degree of resem­ blance between the natural and social sciences has long been the subject of discussion within the social sciences themselves, I do not think the question has been much discussed in these particular terms. Since this issue ofSocialResearch attests to the presence of fruitful errors in the natural sciences, we invited several distinguished social scien­ tists to address the question of whether such errors occur in the social sciences. Many of the social scientists from whom I initially requested advice pointed out that, unlike physical laws in the natural sciences, “laws” in the social sciences—if there are any—are often contin­ gent and change as the social and cultural contexts change. In addi­ tion, two of the respondents pointed out, I think correctly, that the prim ary problem in the social sciences is not so much the validity of the claims of social scientists, which may or not be correct, but rather the consequences of those claims for social policies. An obvi­ ous instance of this was Cyril Burt’s claim about genetic differences in intelligence, which led to discriminatory immigration rules and other bad social policy. Fortunately for us at Sodal Research despite the general consen­ sus that “fruitful” errors were not characteristic of the social sciences, several distinguished social scientists agreed to explore the question of social research Vol 72 : No 1: Spring 2005 xl errors in the social sciences and have written interestingly about it for this issue. These articles stand as illuminating complements to the arti­ cles by historians of the natural sciences that also appear, and clarify one more dimension on which the social and natural sciences differ. Arien Mack xii social research ...

That there are differences between social and natural phenomena is hardly a matter of dispute, and there is little question that these differences result from role of subjective states such as purposes, attitudes, and beliefs in human affairs. The important question is not whether these differences exist but whether they lead to fundamental differences between natural and social sciences. As Bhaskar notes, this is primal question of philosophy of social and it has dominated social sciences since their birth.1 The ardently contested issues raised by question of relationship between social and natural sciences have permeated social-scientific disciplines in disputes that have decisively shaped their development.2 Perhaps it is only a slight exaggeration to suggest that differences between various schools within social sciences are reducible to different ways these issues have been resolved. The framework for discussion of these issues was in large measure work of Max Weber. This is not surprising from a thinker labeled the last universal genius of social sciences3 by an admirer and the greatest social scientist of our century4 by one of his harshest critics. Although Weber's interest in methodological issues was secondary and his writings on subject usually polemical, erudition and insight with which he analyzed character of social sciences have commanded continuing attention. This attention has focused primarily on Weber's insistence that susceptibility of social phenomena to interpretative understanding radically distinguishes them from natural phenomena and creates a unique task for social sciences. This alone, however, says nothing about relationship between social and natural sciences, and no aspect of Weber's thought has been more controversial or more variously construed than nature of interpretative understanding and its significance for logic of sociocultural inquiry.5

Research results in the social and behavioral sciences are often conceded to be less replicable than research results in the physical sciences. However, direct empirical comparisons of the cumulativeness of research in the social and physical sciences have not been made to date. This article notes the parallels between methods used in the quantitative synthesis of research in the social and in the physical sciences. Essentially identical methods are used to test the consistency of research results in physics and in psychology. These methods can be used to compare the consistency of replicated research results in physics and in the social sciences. The methodology is illustrated with 13 exemplary reviews from each domain. The exemplary comparison suggests that the results of physical experiments may not be strikingly more consistent than those of social or behavioral experiments. The data suggest that even the results of physical experiments may not be cumulative in the absolute sense by statistical criteria. It is argued that the study of the actual cumulativeness found in physical data could inform social scientists about what to expect from replicated experiments under good conditions. Psychologists and other social scientists have often compared their fields to the natural (the hard) sciences with a tinge of dismay. Those of us in the social and behavioral sciences know intuitively that there is something softer and less cumulative about our research results than about those of the physical sciences. It is easy to chronicle the differences between soft and hard sciences that might lead to less cumulative research results in the soft sciences. One such chronicle is provided by Meehl (1978), who listed 20 such differences and went on to argue that reliance on tests of statistical significance also contributes to the poorer cumulativeness of research results in the social sciences. Other distinguished researchers have cited the pervasive presence of interactions (Cronbach, 1975) or historical influences (Gergen, 1973, 1982) as reasons not to expect a cumulative social science. Still others (Kruskal, 1978, 1981) have cited the low quality of data in the social sciences as a barrier to truly cumulative social inquiry. These pessimistic views have been accompanied by a tendency to reconceptualize the philosophy of inquiry into a format that implies less ambitious aspirations for social knowledge (e.g., Cronbach, 1975; Gergen, 1982). Cumulativeness in the scientific enterprise can mean at least two things. In the broadest sense scientific results are cumulative if empirical laws and theoretical structures build on one another so that later developments extend and unify earlier work. This idea might be called conceptual or theoretical cumulativeness. The assessment of theoretical cumulativeness must be rather subjective. A narrower and less subjective indicator of cumulativeness is the degree of agreement among replicated experiments or the degree to which related experimental results fit into a simple pattern that makes conceptual sense. This idea might be called empirical cumulativeness. The purpose of this article is to suggest that it may be possible to compare at least the empirical cumulativeness of psychological research with that of research in the physical sciences. An exemplary comparison suggests that the differences may be less striking than previously imagined. The mechanism for this comparison is derived from recent developments in methods for the quantitative synthesis of research in the social sciences. Some of the methods used in meta-analysis are analogous to methods used in the quantitative synthesis of research in the physical sciences. In particular, physicists and psychologists use analogous methods for assessing the consistency of research results, a fact that makes possible comparisons among quantitative reviews in physics and in psychology. One such comparison is reported in this article. This comparison was not chosen in a way that guarantees it to be representative of either social science research or physical science research. However, some effort was exerted to prevent the comparison from obviously favoring one domain or the other, and additional examples are provided to suggest that the case for the empirical cumulativeness of physical science could have been made to look far worse. More data would obviously be needed to support strong conclusions. It seems, however, that the obvious conclusion that the results of physical science experiments are more cumulative than those of social science experiments does not have much empirical sup-

The schools of natural science, especially since Newton, have continuously influenced the social science in two ways. As seen in the example of the systems theory or social Darwinism, many social scientists have got insights from the ideas of natural science. It is quite natural that a scientist discovers a new way of thinking or an implication from a different academic discipline; however, the mainstream social scientists have trapped themselves by confining their science with the methodology obtained from natural science in order to validate it. This paper aims to reveal this methodological trap of social science by showing the influence of natural science to social science in the context of validation and by contrasting the differences between social and natural science issue by issue. The issues raised in this paper include the possibility of the monology and the normal science in social science, the debate over fact-value dichotomy and obtaining objectivity in social science, and the role of science and methodological reductionist issue. Considering such idiosyncrasies of social science, it is claimed that social science should keep its methodological uniqueness and autonomy.

From mobile phones and laptop computers to in vitro fertilization and social networks on the Internet, technological devices, products and services are increasingly shaping the lives of people around the world. The pervasiveness of technology and the underlying science that makes it possible has led to a certain ambivalence: most people trust that ‘science’ will eventually help them to live longer, healthier and happier lives. However, they also feel increasingly uncomfortable about certain new technologies, often those that challenge or improve on ‘nature’. Genetically modified crops, gene therapy, stem cell research, cloning, renewed interest in nuclear power: the list of controversial topics involving science and technology is growing steadily and debates on these topics regularly occupy centre stage in public and political arenas. > …the research process itself constitutes a largely overlooked opportunity for addressing social concerns Policy‐makers have responded by calling for increased attention to be paid to the ethical, legal and social aspects of scientific research and technological developments. In particular, new and emerging areas of research—such as genomics, synthetic biology and nanotechnology—have been accompanied by studies of their broader societal implications as well as public‐engagement efforts, in order to guide research and development in ways that respect societal concerns. Such attempts to shape technological trajectories have traditionally occurred both before scientific research, for example, through research policy, technology assessment or public participation, and afterwards, through regulations or market mechanisms. Although these stages are crucial points at which to intervene, the research process itself constitutes a largely overlooked opportunity for addressing social concerns. Indeed, if one acknowledges the central role that scientific research has in the innovation process, this is an area well worth examining. Shaping technological trajectories will, at some point, include shaping the very research processes that help to characterize them (Fisher et al , 2006). Social and …

Editorial

This study aimed to determine the relationship between social media and social relations among university students, users and non-users of social media. It also aimed to Identify indicators for social workers to enable them to work with to support the social relationships for university students, users of social media, from social and natural science disciplines. The study population comprised the whole student body of HelwanUniversity with all its faculties. The total sample of the research was 210 students, where 95 students were from social science disciplines (specifically Faculty of Social Work and Faculty of Arts), and 115 students were from natural science disciplines (specifically Faculty of Pharmacy and Faculty of Sciences). The study concluded that there are differences between the social media user and non-user students from social science disciplines, and no differences between user and non-user students from natural science disciplines on the social relations scale. However, there are differences between the mean scores of social media non-user students from social science disciplines and those from natural science disciplines on the social relations scale

This article discusses trends in the use of artificial intelligence (AI) in social sciences and natural sciences research. The introduction highlights how AI has evolved into an essential tool in both fields, addressing the limitations of traditional methods in social sciences and accelerating data analysis in natural sciences. The research method used is bibliometric analysis, with data collected from Google Scholar using keywords related to AI in social and natural sciences. Relevant articles were selected through a content evaluation and exclusion process, resulting in 1,000 social science publications and 999 natural science publications, which were further analyzed using VOSviewer with such as being outside the five-year range (published from 2020 to 2025). The study's findings indicate that in social sciences, AI is widely used to enhance research effectiveness through faster data processing, particularly in higher education and social policy analysis. Additionally, AI studies in social sciences are expanding, focusing on ethics, regulation, and human-AI interaction. In natural sciences, AI plays a crucial role in resource management, environmental research, and the healthcare industry, including disease diagnosis and drug development. Recent trends also show an increasing use of large language models (LLMs) and natural language processing (NLP) in scientific research. The study concludes that AI has become a key element in both social and natural science research. Recommendations for social science researchers include further exploration of AI’s impact on psychology, law, and education, as well as the use of bibliometric methods. Meanwhile, natural science researchers are advised to focus on improving AI transparency, developing more accurate technologies, and applying AI in environmental and industrial research. Interdisciplinary collaboration is necessary to ensure AI development remains ethical and inclusive.

The article is devoted to the study of social sciences and social capital in the system of higher education and economy of Ukraine. The article aims to solve two tasks: The first - is to discuss the, not simple, relationship between the natural and social sciences in stimulating technological innovations; The second - is to show how the new concepts of social and cultural capital are connected to economic development. The main results of the article are presented in a study of scientific works devoted to the relationship between the social and natural sciences and how this relationship relates to educational and economic development. The methodological basis of the research is the methods of comparative analysis of scientific research in the field of social and natural sciences, the authors of which investigated human, social and cultural capital. The article also examines the main scientific discussions on the role of social and cultural capital. These are relatively new topics that are increasingly recognized as important components of development. It is stated that the humanities and social sciences should occupy a prominent place in education because, paradoxically, these subjects stimulate technological innovation and economic growth in modern knowledge economies. This view coincides with the school of New Institutional Economics (New Institutional Economics) and the school of "human relations" (human relations) in the field of management, which emphasize social and cultural factors for the effective functioning of organizations and economic development. The technocratic or scientific management paradigm has reached the limits of its usefulness in education, innovation, and economic progress. This paradigm now needs to be supplemented by more open educational systems and organizations, whose functioning is enhanced by cultural and social capital.

A New Field:<i>History of Humanities</i>

Advancing translational research in environmental science: The role and impact of social sciences