Shifting the Level of Selection in Science

How contemporary academic structures constrain scientific creativity and hold back early-career researchers

We argue that contemporary scientific systems progressively constrain high-risk and conceptually innovative research while being increasingly structured around short funding cycles, productivity-based evaluation criteria and risk-averse frameworks that favour predictable and non-transformative research outputs. Drawing on recent empirical literature, we show how such systems can place disproportionate pressure on early-career researchers by incentivizing safe, tractable and easily evaluated outputs. Structural academic mechanisms such as peer review and funding, escalating publication costs and institutional inequalities interact with precarious employment and hierarchical dependencies. In this environment, we contend that strategic conformity becomes a rational career path. This risks suppressing creativity and critical thinking precisely at the stage when scientific independence could otherwise emerge. Consequently, the probability of substantive contributions by early-career researchers is declining, while talent may increasingly abandon academia or cluster within a limited number of well-resourced institutions and national systems. By adopting a systems-level perspective, we argue that scientific creativity is not merely an individual trait but an emerging property of a supportive academic landscape and that maintaining or restoring it may require substantial structural reforms. These include promoting stable research pathways, decentralized decision-making and evaluation frameworks that better recognize collaboration, originality, persistence and nonlinear career trajectories. Without systemic change, we risk stifling the potential of early-career researchers to go beyond the confines of existing methods and approaches and deliver transformative advances. This would limit their capacity to meaningfully change our understanding of the world or benefit society, with impacts that fall short of their potential.

Outcomes Graph: A protocol for applied science coordination - DeepScience Ventures

In this article, we explain how our Outcomes Graph works, including how the functions of scientific knowledge shape the features we've developed and how we're using it to harness the collective intelligence of venture scientists.

A Vision of Metascience

How does the culture of science change and improve? Many people have identified shortcomings in core social processes of science, such as peer review, how grants are awarded, how people are selected to become scientists, and so on. Yet despite often compelling criticisms, strong barriers inhibit widespread change in such social processes. The result is near stasis, and apathy about the prospects for improvement. People sometimes start new research institutions intended to do things differently; unfortunately such institutions are often changed more by the existing ecosystem than they change it. In this essay we sketch a vision of how the social processes of science may be rapidly improved. In this vision, metascience plays a key role: it deepens our understanding of which social processes best support discovery; that understanding can then help drive change. We introduce the notion of a metascience entrepreneur, a person seeking to achieve a scalable improvement in the social processes of science. We argue that: (1) metascience is an imaginative design practice, exploring an enormous design space for social processes; (2) that exploration aims to find new social processes which unlock latent potential for discovery; (3) decentralized change must be possible, so outsiders with superior ideas can't be blocked by established power centers; (4) ideally, change would align with what is best for science and for humanity, not merely what is fashionable, politically popular, or media-friendly; (5) the net result would be a far more structurally diverse set of environments for doing science; and (6) this would enable crucial types of work difficult or impossible within existing environments. For this vision to succeed metascience must develop and intertwine three elements: an imaginative design practice, an entrepreneurial discipline, and a research field. Overall, it is a vision in which metascience is an engine of improvement for the social processes and ultimately the culture of science.

Research topic choice: Motivations, strategies, and consequences

Abstract. Scientists’ choices of what research topics to pursue are highly consequential and have been the subject of many studies. However, these studies are dispersed across several fields and literatures. This paper provides a review of this body of work. It first reviews theory from economics and sociology to explain how topic choice fits into scientists’ broader competitive strategy, and how the social valuation of research topics reproduces inequalities in science. Then it examines empirical literature on how research topics are chosen in practice, first looking at observational accounts derived from large-scale secondary data sources, then looking at self-reported accounts elicited by surveys and interviews of researchers. Finally, it concludes with a synthesis of the theoretical and empirical literature and identifies research gaps. Themes in these literatures include the rewards associated with certain topics, demographic differences in topic choices, and whether choices are broadly reward maximizing or driven by social context, identities, and path dependence. We also identify several research gaps, including the types and impacts of costs impeding topic entry and switching, the causal mechanisms associating topics with rewards, and the discrepancy between scientists’ self-reported topic motivations and observed behavior.

From Grants to Portfolios: Index Logic for Science

How science can learn from capital markets to coordinate diversity, measure progress, and turn discovery into a public portfolio.

Science as Collective Sensemaking

What is Science?

Science as Collective Sensemaking

What is Science?

Claude Team plan for scientists

Scientists at academic and nonprofit research institutions around the world can now get Claude at no cost to start. Shared projects, Claude Science, and admin controls at rates built for grant budgets. 1-seat minimum.

Involuntary collaboration: a strategy for decentralized science

How your best co-worker, might be someone you’ll never meet

Access to Opportunity in the Sciences: Evidence from the Nobel Laureates

Unequal opportunity in the sciences reduces scientific contributions from the most talented individuals and limits the rate of human progress. We study unequal opportunity by collecting data on the childhood SES of Nobel laureates in the sciences. The average laureate grew up in an 87–90th percentile household. Access to opportunity doubled from 1901–2023, but remains highly unequal. Barriers are higher for women, but lower for Americans. Access to opportunity across countries is much less equal, and has barely improved at all. Cities with more intergenerational mobility produce more laureates from non-elite families, and more laureates overall.

How and When to Involve Crowds in Scientific Research - The Book

This book explores how millions of people can significantly contribute to scientific research. Discover main elements, authors, and who this book is for and why.

The Peer Review Crisis Demands Radical Reform: Why Reviewers Should Become Paid Professional Referees

The peer review system, fundamental to scientific quality control, faces a significant crisis. As journal editors, we often need to send up to 35 invitations just to secure two reviewers, confronting daily the collapse of voluntary participation. This reflects a critical imbalance: while publication pressure intensifies, willingness to evaluate diminishes, creating "literature elephantiasis", i.e., an overwhelming proliferation of papers exceeding human processing capacity. Current compensation models, relying on token recognition and database access, fail to incentivize quality engagement and may encourage ethically problematic practices like excessive self-citation. The unchecked infiltration of artificial intelligence into peer review, with minimal enforcement, further undermines system integrity. We propose transforming peer reviewers into professional referees, modeled on sports officiating. This radical solution involves formal training and certification for reviewers, equipping them to assess scientific merit, methodology, and ethics comprehensively. Like sports referees supported by assistants, scientific referees would collaborate with specialists - including statisticians, methodology experts, and reference checkers - ensuring thorough evaluation while distributing workload effectively. Funding would come from publishers or research funders, recognizing peer review as an essential, compensated component of the research lifecycle. Implementation faces challenges including publisher resistance and funding allocation, which we address through phased transition strategies. This professionalization addresses current inequities where conscientious scientists shoulder disproportionate reviewing burdens while others contribute minimally. Professional reviewers would view evaluation as valued career development rather than unwelcome obligation. Critics citing independence concerns overlook the sports analogy: referees maintain impartiality through professional standards despite league compensation. Quality scientific evaluation requires dedicated expertise, adequate training, and fair remuneration. Science deserves better than a system dependent on goodwill and guilt - it needs professional referees now.

More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review | Organization Science

As the AI Task Force for Organization Science, we provide an early account of artificial intelligence’s (AI) impact on both submissions and reviews at a major academic journal. Submission volume ha...