Science of science: A multidisciplinary field studying science.

Science and knowledge are studied by researchers across many disciplines, examining how they are developed, what their current boundaries are and how we can advance them. By integrating evidence across disparate disciplines, the holistic field of can address these foundational questions. This field illustrates how science is shaped by many interconnected factors: the cognitive processes of scientists, the historical evolution of science, economic incentives, institutional influences, computational approaches, statistical, mathematical and instrumental foundations of scientific inference, scientometric measures, philosophical and ethical dimensions of scientific concepts, among other influences.

Redefining the scientific method: as the use of sophisticated scientific methods that extend our mind.

Scientific, medical, and technological knowledge has transformed our world, but we still poorly understand the nature of scientific methodology. Science textbooks, science dictionaries, and science institutions often state that scientists follow, and should follow, the universal scientific method of testing hypotheses using observation and experimentation. Yet, scientific methodology has not been systematically analyzed using large-scale data and scientific methods themselves as it is viewed as not easily amenable to scientific study.

Early-career factors largely determine the future impact of prominent researchers: evidence across eight scientific fields.

Can we help predict the future impact of researchers using early-career factors? We analyze early-career factors of the world's 100 most prominent researchers across 8 scientific fields and identify four key drivers in researchers' initial career: working at a top 25 ranked university, publishing a paper in a top 5 ranked journal, publishing most papers in top quartile (high-impact) journals and co-authoring with other prominent researchers in their field. We find that over 95% of prominent researchers across multiple fields had at least one of these four features in the first 5 years of their career. We find that the most prominent scientists who had an early career advantage in terms of citations and h-index are more likely to have had all four features, and that this advantage persists throughout their career after 10, 15 and 20 years.

Homo methodologicus and the origin of science and civilisation.

Few things have impacted our lives as much as science and technology, but how we developed science and civilisation is one of the most challenging questions that has not yet been well explained. Attempting to identify the central driver, leading scientists have highlighted the role of culture, cooperation and geography. They focus thus on factors that are important basic preconditions but that we cannot directly influence.

Generalization Bias in Science.

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account.

Master stability functions for metacommunities with two types of habitats.

Current questions in ecology revolve around instabilities in the dynamics on spatial networks and particularly the effect of node heterogeneity. We extend the master stability function formalism to inhomogeneous biregular networks having two types of spatial nodes. Notably, this class of systems also allows the investigation of certain types of dynamics on higher-order networks.

Measures of effectiveness in medical research: Reporting both absolute and relative measures.

Biomedical research, especially pharmaceutical research, has been criticised for engaging in practices that lead to over-estimations of the effectiveness of medical treatments. A central issue concerns the reporting of absolute and relative measures of medical effectiveness. In this paper we critically examine proposals made by Jacob Stegenga to (a) give priority to the reporting of absolute measures over relative measures, and (b) downgrade the measures of effectiveness (effect sizes) of the treatments tested in clinical trials (Stegenga, 2015a).

Explaining public understanding of the concepts of climate change, nutrition, poverty and effective medical drugs: An international experimental survey.

Climate change, nutrition, poverty and medical drugs are widely discussed and pressing issues in science, policy and society. Despite these issues being of great importance for the quality of our lives it remains unclear how well people understand them. Specifically, do particular demographic and socioeconomic factors explain variation in public understanding of these four concepts? To what extent are people's changes in understanding associated with changes in their behaviour? Do people judge scientific practices relying on the more descriptive concepts of climate change and effective medical drugs to be more objective (less controversial) than practices relying on the more value-laden concepts of poverty and healthy nutrition? To address these questions, an experimental survey and regression analyses are conducted using data collected from about one thousand participants across different continents.

Why all randomised controlled trials produce biased results.

Background: Randomised controlled trials (RCTs) are commonly viewed as the best research method to inform public health and social policy. Usually they are thought of as providing the most rigorous evidence of a treatment's effectiveness without strong assumptions, biases and limitations.

Objective: This is the first study to examine that hypothesis by assessing the 10 most cited RCT studies worldwide.