Crediting non-author contributors in scientific publishing
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Evolution and impact of the science of science: from theoretical analysis to digital-AI driven research
The Science of Science (SoS) examines the mechanisms driving the development and societal role of science, evolving from its sociological roots into a data-driven discipline. This paper traces the progression of SoS from its early focus on the social functions of science to the current era, characterized by large-scale quantitative analysis and AI-driven methodologies. Scientometrics, a key branch of SoS, has utilized statistical methods and citation analysis to understand scientific growth and knowledge diffusion. With the rise of big data and complex network theory, SoS has transitioned toward more refined analyses, leveraging artificial intelligence (AI) for predictive modeling, sentiment annotation, and entity extraction. This paper explores the application of AI in SoS, highlighting its role as a surrogate, quant, and arbiter in advancing data processing, data analysis and peer review. The integration of AI has ushered in a new paradigm for SoS, enhancing its predictive accuracy and providing deeper insights into the internal dynamics of science and its impact on society.
Third-party evaluators perceive AI as more compassionate than expert humans
Empathy connects us but strains under demanding settings. This study explored how third parties evaluated AI-generated empathetic responses versus human responses in terms of compassion, responsiveness, and overall preference across four preregistered experiments. Participants (N = 556) read empathy prompts describing valenced personal experiences and compared the AI responses to select non-expert or expert humans. Results revealed that AI responses were preferred and rated as more compassionate compared to select human responders (Study 1). This pattern of results remained when author identity was made transparent (Study 2), when AI was compared to expert crisis responders (Study 3), and when author identity was disclosed to all participants (Study 4). Third parties perceived AI as being more responsive—conveying understanding, validation, and care—which partially explained AI’s higher compassion ratings in Study 4. These findings suggest that AI has robust utility in contexts requiring empathetic interaction, with the potential to address the increasing need for empathy in supportive communication contexts.
Toward change in the uneven geographies of urban knowledge production
More than four-fifths of the global urban population live in the Global South and East. Most urban theories, however, originate in the Global North. Building on recent efforts to address this mismatch, this paper examines the geographies of urban knowledge production. It analyzes the institutional affiliations of contributions in 25 leading Anglophone journals (n = 14,582) and nine urban handbooks (n = 252). We show that 42% of the journal articles and 17% of the handbook chapters were authored outside the Global North. However, only 15% of the editor positions (handbooks: 10%) were held by scholars based outside the Global North. This indicates that Global Northern institutions still dominate knowledge gatekeeping, whereas authors are more diverse. Additionally, more empirical journals and those with fewer Northern board members tend to publish more non-Northern authors. Our findings underscore the need for greater epistemic diversity in gatekeeping positions and broader understandings of what counts as theory to better incorporate diverse urban knowledge.
Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
A manifesto for a globally diverse, equitable, and inclusive open science
The field of psychology has rapidly transformed its open science practices in recent years. Yet there has been limited progress in integrating principles of diversity, equity and inclusion. In this Perspective, we raise the spectre of Questionable Generalisability Practices and the issue of MASKing (Making Assumptions based on Skewed Knowledge), calling for more responsible practices in generalising study findings and co-authorship to promote global equity in knowledge production. To drive change, researchers must target all four key components of the research process: design, reporting, generalisation, and evaluation. Additionally, macro-level geopolitical factors must be considered to move towards a robust behavioural science that is truly inclusive, representing the voices and experiences of the majority world (i.e., low-and-middle-income countries).
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