Related papers: Flat Teams Drive Scientific Innovation
While the modern science is characterized by an exponential growth in scientific literature, the increase in publication volume clearly does not reflect the expansion of the cognitive boundaries of science. Nevertheless, most of the metrics…
Purpose: The purpose of this paper is to explore possible factors impacting team performance in healthcare, by focusing on information exchange within and across hospital's boundaries. Design/methodology/approach: Through a web-survey and…
Geographically distributed teams often face challenges in coordination and collaboration, lowering their productivity. Understanding the relationship between team dispersion and productivity is critical for supporting such teams. Extensive…
Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally distributed. Here we test whether large language models (LLMs) can contribute to this…
Throughout history, a relatively small number of individuals have made a profound and lasting impact on science and society. Despite long-standing, multi-disciplinary interests in understanding careers of elite scientists, there have been…
The participation of women in academia has increased in the last few decades across many fields (e.g., Computer Science, History, Medicine). However, this increase in the participation of women has not been the same at all career stages.…
We approach productivity in science in a longitudinal fashion: We track careers over time, up to 40 years. We first allocate scientists to decile-based publishing productivity classes, from the bottom 10% to the top 10%. Then, we seek…
We explore a paradox of collective action and certainty in science wherein the more scientists research together, the less that work contributes to the value of their collective certainty. When scientists address similar problems and share…
As artificial intelligence advances, models are not improving uniformly. Instead, progress unfolds in a jagged fashion, with capabilities growing unevenly across tasks, domains, and model scales. In this work, we examine this dynamic…
Research institutions provide the infrastructure for scientific discovery, yet their role in the production of knowledge is not well characterized. To address this gap, we analyze interactions of researchers within and between institutions…
Large language models (LLMs) are increasingly transforming biomedical discovery and clinical innovation, yet their impact extends far beyond algorithmic revolution-LLMs are restructuring how scientific collaboration occurs, who…
This work verifies whether research diversification by a scientist is in some measure related to their collaboration with multidisciplinary teams. The analysis considers the publications achieved by 5300 Italian academics in the sciences…
Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the…
In a range of scientific coauthorship networks, transitions emerge in degree distributions, correlations between degrees and local clustering coefficients, etc. The existence of those transitions could be regarded as a result of the…
Scientific discovery is shaped by scientists' choices and thus by their career patterns. The increasing knowledge required to work at the frontier of science makes it harder for an individual to embark on unexplored paths. Yet…
Science is a cumulative activity, which can manifest itself through the act of citing. Citations are also central to research evaluation, thus creating incentives for researchers to cite their own work. Using a dataset containing more than…
We discuss a recently proposed family of statistical network models - relational hyperevent models (RHEM) - for analyzing team selection and team performance in scientific coauthor networks. The underlying rationale for using RHEM in…
Large language model (LLM)-based systems are increasingly deployed to conduct scientific research autonomously, yet whether their reasoning adheres to the epistemic norms that make scientific inquiry self-correcting is poorly understood.…
Human culture relies on innovation: our ability to continuously explore how existing elements can be combined to create new ones. Innovation is not solitary, it relies on collective search and accumulation. Reinforcement learning (RL)…
As the increasing complexity of large-scale research requires the combined efforts of scientists with expertise in different fields, the advantages and costs of interdisciplinary scholarship have taken center stage in current debates on…