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.
Faster science, penalties in evaluation, and concerns on quality and impact: Researchers’ use and perceptions of preprints
The preprint ecosystem has expanded rapidly over the past decade, fundamentally altering science communication. Yet, the scholarly community’s attitudes toward this shift remain underexplored. Through a large-scale survey of US and Canadian biomedical scholars, we provide a comprehensive analysis of preprint utilization, perceived impact, and integration into academic credit systems. We find robust engagement across reading, citing, and submitting preprints; however, this activity is driven primarily by a desire for rapid dissemination rather than a foundational commitment to open science. Furthermore, while preprints are valued as networking assets, perceived career penalties during formal academic evaluations stifle broader cultural adoption. Crucially, to navigate the absence of formal peer review, scholars report a heavy reliance on author reputation as a primary heuristic to evaluate a preprint’s credibility and guide their reading and citation decisions. Notably, despite acknowledging preprints’ role in accelerating knowledge sharing, scholars express significant concerns regarding fraud and misinformation, particularly amid declining public trust in science and emerging threats to scientific integrity from artificial intelligence. To resolve these tensions, the preprint ecosystem must evolve beyond prioritizing speed to foster genuine academic dialogue. Simultaneously, evaluation frameworks must adapt to the realities of preprinting, and innovative quality-control mechanisms are urgently needed to balance rapid dissemination with rigorous scientific integrity.
The Human Infrastructure of Open Science: Why Mentorship Matters More Than Ever
The transformation of academia into a more open and inclusive ecosystem depends not only on new policies or technologies but also on a fundamental shift in how we nurture early-career researchers through mentorship. This values resilience and integrity as much as productivity. Introduction In the vast, often complex, competitive, and
Shifting the Level of Selection in Science
Criteria for recognizing and rewarding scientists primarily focus on individual contributions. This creates a conflict between what is best for scientists’ careers and what is best for science. In this article, we show how the theory of multilevel selection provides conceptual tools for modifying incentives to better align individual and collective interests. A core principle is the need to account for indirect effects by shifting the level at which selection operates from individuals to the groups in which individuals are embedded. This principle is used in several fields to improve collective outcomes, including animal husbandry, team sports, and professional organizations. Shifting the level of selection has the potential to ameliorate several problems in contemporary science, including accounting for scientists’ diverse contributions to knowledge generation, reducing individual-level competition, and promoting specialization and team science. We discuss the difficulties associated with shifting the level of selection and outline directions for future development in this domain.
The Discovery Engine: A Framework for AI-Driven Synthesis and Navigation of Scientific Knowledge Landscapes
Scientific progress relies on the effective accumulation, synthesis, and critical evaluation of knowledge. Traditionally, the well-documented, peer reviewed publication served as the primary standard for filtering and disseminating credible findings within the scientific community. Recently, however, we are witnessing an unprecedented acceleration in research output, a veritable explosion of scientific publications across all disciplines [1]. Yet, this very abundance creates a paradox: the sheer volume threatens to overwhelm the mechanisms designed for its assimilation and synthesis. Researchers, even within highly specialized subfields, face an almost insurmountable challenge in keeping abreast of relevant developments, integrating disparate findings, and identifying the truly novel signals amidst the noise [2]. This information overload contributes to disciplinary fragmentation, hindering the cross-pollination of ideas essential for disruptive innovation [3]. Furthermore, persistent concerns regarding "reproducibility crisis" [2], predatory journals, inflation of research areas[4], growing retractions and the potential influences of bibliometrics on research direction [5] highlight systemic challenges in validating and prioritizing scientific contributions to fundamental knowledge.
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.
A New Paradigm for Scientific Publishing, Peer Review, and Impact Assessment
Scientific publishing and peer review have evolved little in three centuries, while the demands placed on them have grown profoundly. The growing role of artificial intelligence has underscored deep, systemic shortcomings of an aging system that has largely evaded innovation, a system whose origins are appallingly closer to the invention of the printing press than to the internet. We can do better – much better. This article is intended as the beginning of a communal experiment: a living document that critically reviews the modern academic publishing and peer-review system and presents a concrete framework to address what bibliometrics experts¹ have characterized as "the pervasive misapplication of indicators to the evaluation of scientific performance". Building on the Leiden Manifesto, DORA, and a body of scholarship spanning many disciplines and decades, we present a community-governed, non-profit platform organized around three trust-weighted impact factors, for articles, authors, and reviewers, with full algorithmic transparency, an open development log, and structural decoupling of credibility scoring from content moderation and from monetization. We invite the community to discuss, critique, and help shape it.
Reformation of science publishing: the Stockholm Declaration
Science relies on integrity and trustworthiness. But scientists under career pressure are lured to purchase fake publications from ‘paper mills’ that use AI-generated data, text and image fabrication. The number of low-quality or fraudulent publications is rising to hundreds of thousands per year, which—if unchecked—will damage the scientific and economic progress of our societies. The result is editor and reviewer fatigue, irreproducible experiments, misguided experiments, disinformation and escalating costs that devour funding from taxpayers intended for research. It is high time to reevaluate current publishing models and outline a global plan to stop this unhealthy development. A conference was therefore organized by the Royal Swedish Academy of Sciences to draft an action plan with specific recommendations, as follows. (i) Academia should resume control of publishing using non-profit publishing models (e.g. diamond open-access). (ii) Adjust incentive systems to merit quality, not quantity, in a reputation economy where the gaming of publication numbers and citation metrics distorts the perception of academic excellence. (iii) Implement mechanisms to prevent and detect fake publications and fraud which are independent of publishers. (iv) Draft and implement legislations, regulations and policies to increase publishing quality and integrity. This is a call to action for universities, academies, science organizations and funders to unite and join this effort.
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.
AI and the Future of Science
Reclaiming scientific publishing: Our duty to make science freely accessible to all
When we (Camille Thomas and Romain Vaucher speaking) entered academia as graduate students in France and Switzerland, we were enthusiastic about the vast amount of research available with a simple click on our university computers. However, we also quickly felt disheartened by the significant amount of research work we couldn’t access when wrapping up our theses from home. Luckily, pirates existed. Empowered by Aaron Swartz’s Guerilla Open Access Manifesto, Alexandra Elbakyan created Sci-Hub in 2011, the greatest leak of scientific knowledge of the century. We felt right in the middle of an Open Access (OA) revolution that would finally make all scientific articles, old and new, accessible to everyone. Fifteen years later, our hopes as idealistic early-career researchers have been crushed by the oligopolistic model of scientific publishing and the subtle pressures of the “publish or perish” culture that reigns over our career development. In the meantime, publishers like Frontiers, MDPI and Springer Nature, to name a few, have exponentially expanded their number of titles. They have become increasingly exploitative of scholarly manpower, moving far away from the genuine accessibility they allegedly promised under the guise of this OA transformation. Open Access is to be praised, but the way it has been implemented through the mainstream Gold and Green OA models now primarily serves the status quo of large for-profit publishers. These entities hijack public money and voluntary editorial labour for their own profit and that of their shareholders (Butler et al., 2023; Shu and Larivière, 2024). In a nutshell, to offer reader accessibility, the Gold OA model requires authors to pay an Article Processing Charge (APC; around 2,000 $/€, rarely less, and often much more) covered by individual research funds, funding agencies or university library deals. The Green OA model allows authors to upload their accepted, non-formatted manuscripts to repositories after an embargo period. While both models allow compliance with funding agency mandates, true equity and accessibility are ultimately left behind. In an article we recently published (Vaucher and Thomas, 2026), we describe the mechanisms through which we, as researchers, inadvertently contribute to keeping research exclusive while driving the publishing model down an unsustainable path. Just like our broader economy, our publishing model and the ways science is evaluated fuelled a predatory system that demands more papers, funding and prestige at an ever-faster rate (Walter and Mullins, 2019), likely at the expense of quality, diversity and ethics (Frank et al., 2023; Heen and Vogt, 2024). These concerns aren’t entirely new. What is new, however, is the growing realisation among societies, universities and funding bodies that we must move away from this system. Initiatives like the European Diamond Capacity Hub, ALMASI and craft-OA are actively paving a way forward that we, as scientists, have yet to fully embrace. In the geosciences, a collective and concerted effort is currently being made by researchers to provide fairer, more sustainable alternatives through community-driven Diamond OA journals (which feature no APCs and completely free access to published articles). Volcanica (Farquharson and Wadsworth, 2018), Sedimentologika (Thomas et al., 2023), Tektonika (Fernández-Blanco et al., 2023), Seismica (Rowe et al., 2022), Geomorphica (Lefebvre et al., 2025), Open Paleontology (Drage et al., 2024), Advances in Geochemistry and Cosmochemistry (Pourret et al., 2025), Geodynamica, jSEDI and Planetary Research are all recently created, scholarly-run journals funded by university library investments to promote better ways of publishing. Their articles are peer-reviewed, free for readers to access, and free for authors to publish. They rely entirely on the voluntary involvement of scientists running open-source editorial platforms (such as Open Journal Systems), transparent workflows, copyediting, production and final dissemination. Diamond OA journals offer an alternative path for all of us to transform our broken publishing system and reclaim ownership of our own science. These efforts go hand in hand with greater involvement in our academic societies and non-profit publishing initiatives. Ultimately, real transformation can only happen if all of us as researchers realise how inherently unfair and exclusive the current system is to labs and institutions that cannot afford steep Gold OA APCs or paywalled journal subscriptions. It also means we must collectively stop evaluating science based on journal prestige and the flawed metrics they own (Posada and Chen, 2018; Sabel and Larhammar, 2025; Simons, 2008). Only by breaking these habits can we truly make knowledge accessible to all. References Butler, L.-A., Matthias, L., Simard, M.-A., Mongeon, P., and Haustein, S.: The oligopoly’s shift to open access: How the big five academic publishers profit from article processing charges, Quantitative Science Studies, 4, 778–799, https://doi.org/10.1162/qss_a_00272, 2023. Drage, H. B., Keating, J. N., Nielsen, M. L., Saleh, F., and Hearing, T. W. W.: Open Palaeontology: a new model of diamond open access journal for palaeontology, Open Palaeontology, 1, 1–6, https://doi.org/10.26034/la.opal.2024.6223, 2024. Farquharson, J. I. and Wadsworth, F. B.: Introducing Volcanica: The first diamond open-access journal for volcanology, Volcanica, 1, I–IX, https://doi.org/10.30909/vol.01.01.i-ix, 2018. Fernández-Blanco, D., Lacassin, R., Gouiza, M., Perez-Diaz, L., Magee, C., McCarthy, D., Doré, T., Péron-Pinvidic, G., Kavanagh, J., Bond, C., and Schmitt, R.: Tektonika: The Community-Led Diamond Open-Access Journal for Tectonics and Structural Geology, τeκτoniκa, 1, I–XIII, https://doi.org/10.55575/tektonika2023.1.1.56, 2023. Frank, J., Foster, R., and Pagliari, C.: Open access publishing – noble intention, flawed reality, Social Science & Medicine, 317, 115592, https://doi.org/10.1016/j.socscimed.2022.115592, 2023. Heen, E. and Vogt, H.: Scientific rot: Unsustainable publishing practices threatens trust in medicine, Journal of Evaluation in Clinical Practice, 30, 941–944, https://doi.org/10.1111/jep.13989, 2024. Lefebvre, A., Bosch, R., Burrows, K., Giaime, M., Goodwin, G., Lai, L. S.-H., Stammler, M., and Fernández, R.: Geomorphica: The most accessible journal for the geomorphology community, Geomorphica, 1, https://doi.org/10.59236/geomorphica.v1i1.54, 2025. Posada, A. and Chen, G.: Inequality in Knowledge Production: The Integration of Academic Infrastructure by Big Publishers, in: ELPUB 2018, https://doi.org/10.4000/proceedings.elpub.2018.30, 2018. Pourret, O., Millet, M.-A., Marin-Carbonne, J., Mallik, A., Tierney, J. E., Darling, J. R., Kiseeva, E. S., Torres, M. A., Fonseca, R. O. C., Tartèse, R., Namur, O., Klöcking, M., Matthews, S. W., Dahrén, B., Ickert, R. B., and Board, the inaugural A. in G. and C. editorial: Equitable Access, Open Science, and the Future of Publishing in Geochemistry and Cosmochemistry, Advances in Geochemistry and Cosmochemistry, 1, https://doi.org/10.33063/agc.v1i1.770, 2025. Rowe, C., Agius, M., Convers, J., Funning, G., Galasso, C., Hicks, S., Huynh, T., Lange, J., Lecocq, T., Mark, H., Okuwaki, R., Ragon, T., Rychert, C., Teplitzky, S., and Van den Ende, M.: The launch of Seismica: a seismic shift in publishing, Seismica, 1, https://doi.org/10.26443/seismica.v1i1.255, 2022. Sabel, B. and Larhammar, D.: Reformation of science publishing: the Stockholm Declaration, R Soc Open Sci., 12, 251805, https://doi.org/10.1098/rsos.251805, 2025. Shu, F. and Larivière, V.: The oligopoly of open access publishing, Scientometrics, 129, 519–536, https://doi.org/10.1007/s11192-023-04876-2, 2024. Simons, K.: The Misused Impact Factor, Science, 322, 165–165, https://doi.org/10.1126/science.1165316, 2008. Thomas, C., Privat, A., Vaucher, R., Spychala, Y., Zuchuat, V., Marchegiano, M., Poyatos-Moré, M., Kane, I., and Chiarella, D.: Sedimentologika: a community-driven diamond open access journal in sedimentology, Sedimentologika, 2023. Vaucher, R. and Thomas, C.: Diamond is the new Green—Why Green Open Access is not a sustainable long-term model for scientific publishing, Sedimentologika, 4, https://doi.org/10.57035/journals/sdk.2026.e41.2397, 2026. Walter, P. and Mullins, D.: From symbiont to parasite: the evolution of for-profit science publishing, Molecular Biology of the Cell, https://doi.org/https://doi.org/10.1091/mbc.E19-03-0147, 2019.
Screening, sorting, and the feedback cycles that imperil peer review
Scholarly journals rely on peer review to identify the science most worthy of publication. Yet finding willing and qualified reviewers to evaluate manuscripts has become an increasingly challenging task, possibly even threatening the long-term viability of peer review as an institution. What can or should be done to salvage it? Here, we develop mathematical models to reveal the intricate interactions among incentives faced by authors, reviewers, and readers in their endeavors to identify the best science. Two facets are particularly salient. First, peer review partially reveals authors’ private sense of their work’s quality through their decisions of where to send their manuscripts. Second, journals’ reliance on traditionally unpaid and largely unrewarded review labor deprives them of a standard market mechanism—wages—to recruit additional reviewers when review labor is in short supply. We highlight a resulting feedback loop that threatens to overwhelm the peer review system: (1) an increase in submissions overtaxes the pool of suitable peer reviewers; (2) the accuracy of review drops because journals must either solicit assistance from less qualified reviewers or ask current reviewers to do more; (3) as review accuracy drops, submissions further increase as more authors try their luck at venues that might otherwise be a stretch. We illustrate how this cycle is propelled by the increasing emphasis on high-impact publications, the proliferation of journals, and competition among these journals for peer reviews. Finally, we suggest interventions that could slow or even reverse this cycle of peer-review meltdown.
The strain on scientific publishing
Scientists are increasingly overwhelmed by the volume of articles being published. Total articles indexed in Scopus and Web of Science have grown exponentially in recent years; in 2022 the article total was approximately ~47% higher than in 2016, which has outpaced the limited growth - if any - in the number of practising scientists. Thus, publication workload per scientist (writing, reviewing, editing) has increased dramatically. We define this problem as the strain on scientific publishing. To analyse this strain, we present five data-driven metrics showing publisher growth, processing times, and citation behaviours. We draw these data from web scrapes, requests for data from publishers, and material that is freely available through publisher websites. Our findings are based on millions of papers produced by leading academic publishers. We find specific groups have disproportionately grown in their articles published per year, contributing to this strain. Some publishers enabled this growth by adopting a strategy of hosting special issues, which publish articles with reduced turnaround times. Given pressures on researchers to publish or perish to be competitive for funding applications, this strain was likely amplified by these offers to publish more articles. We also observed widespread year-over-year inflation of journal impact factors coinciding with this strain, which risks confusing quality signals. Such exponential growth cannot be sustained. The metrics we define here should enable this evolving conversation to reach actionable solutions to address the strain on scientific publishing.
What Next for Academia?
As research agents autonomously synthesize prior work, who gets the credit -- and what keeps talented people in academia when its incentives run on credit?
The unintended consequences of large language models as a labor-augmenting technology in science
As a labor-augmenting technology, large language models (LLMs) have the potential to accelerate scientific activity across the research pipeline. But even if LLMs perform on par with human experts at selected tasks, their use will bring unintended consequences as they alter the balance of frictions and inducements that steer the allocation of research effort across projects. Here we develop a simple mathematical model to illustrate. In fields where LLMs are useful primarily as tools for discovering promising projects, researchers will become more selective about what they publish; where they facilitate the process of publishing existing data, researchers will become less selective. By allowing scientists to work more quickly, LLMs raise the opportunity cost of researcher time, creating incentives to refine papers less thoroughly before moving on. Enticing as it is to imagine that, by saving us time on mundane tasks, LLMs will provide us with more time to think deeply and develop projects completely, our results temper such hopes.
The unintended consequences of large language models as a labor-augmenting technology in science
As a labor-augmenting technology, large language models (LLMs) have the potential to accelerate scientific activity across the research pipeline. But even if LLMs perform on par with human experts at selected tasks, their use will bring unintended consequences as they alter the balance of frictions and inducements that steer the allocation of research effort across projects. Here we develop a simple mathematical model to illustrate. In fields where LLMs are useful primarily as tools for discovering promising projects, researchers will become more selective about what they publish; where they facilitate the process of publishing existing data, researchers will become less selective. By allowing scientists to work more quickly, LLMs raise the opportunity cost of researcher time, creating incentives to refine papers less thoroughly before moving on. Enticing as it is to imagine that, by saving us time on mundane tasks, LLMs will provide us with more time to think deeply and develop projects completely, our results temper such hopes.
Scientific production in the era of Large Language Models
Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and 246M online accesses to scientific documents. We find: 1) scientists adopting LLMs to draft manuscripts demonstrate a large increase in paper production, ranging from 23.7-89.3% depending on scientific field and author background, 2) LLM use has reversed the relationship between writing complexity and paper quality, leading to an influx of manuscripts that are linguistically complex but substantively underwhelming, and 3) LLM adopters access and cite more diverse prior work, including books and younger, less-cited documents. These findings highlight a stunning shift in scientific production that will likely require a change in how journals, funding agencies, and tenure committees evaluate scientific works.