Sociologists face the pressing question of how large language model-based technologies can contribute to social theorising. Several social scientists have called for a greater integration of generative AI tools in the social sciences and humanities to speed and scale up the production of social theory. In this article, we adopt a more cautious approach, reflecting on how the adoption of generative AI raises foundational questions about the construction, refinement and evaluation of critical social theory. To make this argument, we create and critically analyse a speculative piece of dystopian sociological fiction. This enables us to explore the values and practices of critical social theory authorship. We argue that authorship must be ‘recentred’, particularly with regard to four key values of authorial practice: (1) standpoint, (2) creativity, (3) pluralism and (4) accountability. In the present moment, the use of generative AI as substitution for authorial practices redefines and potentially threatens authorship in ways that problematises its particular use in generating critical social theory. With regards to standpoint, generative AI technologies run the risk of reproducing an ‘abstract masculinity’ that feminist scholars have long written against. The relational wonder at the heart of social theory creativity is undermined by generative AI use, as is the pluralism of creativity. Generative AI also flattens and overlooks pluralism of voice, as well as dilutes authorial accountability. We sociologists need to defend and rearticulate what we contribute to social theory and its concomitant politics, both in the theories themselves and in the project of social theorising. It is with this in mind that we call for the ‘rebirth’ - that is, the recentralisation - of the human author in critical social theory creation.
Most countries today have below-replacement fertility and the global population is projected to decline before the century’s end. Potential consequences include fiscal challenges of an aging population, slower economic growth, and weakened kinship networks. Yet the policy response of demographers has been relatively muted compared to their more active role in promoting population control during periods of rapid growth. While substantive considerations help explain disagreement over whether low fertility is a problem, this paper examines how competing moral frameworks—rooted in Social Justice and Social Order—may also shape public and academic responses to low fertility. I begin with a historical comparison between the politics of population growth and today’s debate about population decline and develop a framework linking moral orientations to different understandings of demographic change and appropriate policy responses. I then use large language models to analyze the moral framing of fertility research published in eight leading demographic journals from 1947 to 2025. While most article abstracts contained neither moral frame, among those that did, 83
This comment examines Schroeder, Thelwall, and Thomas’s use of artificial intelligence to operationalize Randall Collins’s sociology of philosophy. While their methodological approach is innovative, I argue that their analysis introduces a significant theoretical distortion. An AI-generated summary replaces Collins’s concept of “structural crunch”, competition for a limited number of positions within a relatively autonomous intellectual attention space,with a broader claim that philosophical prominence depends on cultural relevance and resonance with social change.This shifts the analysis from Collins’s predominantly internalist account toward a more externalist explanation of intellectual prominence and affects the resulting predictions of future philosophical eminence. The case illustrates abroader methodological risk: when large language models are used to operationalize social theory, theoretically distinctive mechanisms may be replaced by more generic and intuitively plausible propositions, thereby modifying the theory they are intended to apply.
Recent years have witnessed many strong claims that ‘diversity’ leads to more original and impactful science, which is a science-focused form of what we call “The Diversity Hypothesis.” However, what evidence supports the claim that diversity enhances scientific output or impact? This pre-registered rapid scoping review seeks to collate and evaluate the scientific evidence for the Diversity Hypothesis as a foundation for future, methodologically rigorous studies that address the Diversity Hypothesis. Guided by the Joanna Briggs Institute approach and Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR), a systematic search of three electronic databases (Web of Science, Scopus, and Ovid PsycInfo) was performed. The Mixed Methods Assessment Tool was used for quality appraisal of included articles. Studies were included if they were peer-reviewed, empirical studies that satisfied the population (‘scientists or scientific teams/labs’), concept (‘diversity of scientists or scientific teams/labs’), context (‘scientific productivity or impact’) as well as other inclusion criteria. In total, 104 articles were included and their findings pertaining to the relationship between diversity and scientific productivity and impact analysed. We estimate that only between 15
