This session will hear findings from six recent studies of different aspects of research funding systems. Topics will include: incentives and accountabilities for data sharing; use of promotional language in proposals; large-scale thematic funding; and research funding landscape analysis.
Long Abstract
Money talks, and when it does it influences many of the things that researchers do and say. This session comprises six papers looking at different aspects of the funder-researcher interaction. Anna Catharina Vieira Armond explores the challenges different funders face in formulating consistent requirements for data management and sharing plans, while Thomas Klebel examines how the complex interplay between funding structures, incentives, and researchers' strategic adaptations may ultimately inhibit data sharing behaviours.
Problems with a lack of consistency are also apparent from an examination of the collection and use of EDI data by funding agencies. Yohanna Juk discusses how a lack of clear communication likely frustrates efforts to create a more diverse and inclusive academy.
Turning to the question of the influence funders on research, Aruhan Bai presents results from a which found that a large grant scheme in China enhanced the subsequent funding and citation rates of funded researchers, but was curiously associated with lower disruption indices. In the same territory, Emer Brady discusses the results of an ongoing investigation of how targeted (as opposed to non-targeted) funding shifts research activity.
And finally, Huilian Sophie Qiu looks at the impact of researchers on funders. Her paper reports that the use of promotional language in grant applications is associated with substantially higher odds of winning funding and asks: is such language warranted or does it sustain biases within the research community?
A Data Management and Sharing Plan (DMSP) guides data handling, preservation, and sharing. This review analyzed Research Data Management (RDM) and DMSP expectations from biomedical funders. Findings highlight the need for standardized guidance to improve clarity, compliance, and data practices.
Long abstract
Background: A Data Management and Sharing Plan (DMSP) outlines how data will be handled, preserved, and shared. Many funders now require DMSPs in their research mandates. However, while there might be consensus on the core elements of a DMSP, specific requirements vary across funders. Therefore, this study aim was to conduct a scoping review to identify and analyze the Research Data Management RDM and DMSP expectations and guidance from biomedical research funders. Methods: We collected data from the major global biomedical funders from the list: www.healthresearchfunders.org. Relevant documents were retrieved from the funders’ websites and supplemented with a Google search. We included statements, policy documents, DMSP templates and examples, guidelines, or grant requirements that included RDM information. Results: A total of 264 funders were included in the analysis. After full-text screening, 196 documents from 84 funders were included. Our findings show that 77 (29%) of the 264 included funders have data-sharing expectations, either as a mandate or recommendation, while 65 (25%) expect a DMSP submission. Where DMPS are expected, 42 (65%) described how they will evaluate and monitor the DMSPs. Additionally, 56 (86%) of these funders provided information about what elements should be included in a DMSP, with differences in the elements they mandate, ranging from basic guidelines to comprehensive requirements. Conclusion: While many funders promote proper data management and sharing, the lack of standardized guidance may create challenges for researchers. Harmonization of DMSP requirements could improve clarity and compliance, and support more effective research data management and sharing practices.
Funding agencies (FA) play a crucial role in addressing inequality in research by collecting diversity data. This study maps ten FAs accountability initiatives using an original framework. Findings show varying transparency levels while others face greater obstacles and slower progress.
Long abstract
Fighting inequality in the research ecosystem has become a key concern for scientists, universities, editorial bodies, and research institutions. Funding agencies (FAs) play a crucial role in addressing these disparities, particularly in how they collect, monitor, and disseminate diversity data, contributing to metascience studies.
While Equity, Diversity, and Inclusion (EDI) initiatives face increasing political scrutiny, such as the recent approach by the government of the US targeting EDI practices as discriminatory and wasteful, and removing EDI data and communication from federal government agencies, the literature demonstrates that accountability and public access to diversity data are essential for fostering research and informing policies that promote EDI in academia.
This study maps the accountability initiatives of FAs regarding diversity data. Based on a literature review and benchmarking of previous studies, we developed categories to assess whether and how ten FAs collect EDI data on applicants, grantees, reviewers, and decision boards, and whether and how aggregated data are publicly available.
Preliminary results suggest that the majority of the analyzed FAs are enhancing communication with stakeholders to improve transparency. Agencies from Australia, Canada, Chile, Switzerland, the UK, and the US report diversity data availability. Notably, FAs from the UK and Chile employ interactive platforms such as Tableau and Power BI, enabling intersectional evaluations, data visualization, and public data exportation. The absence of clear communication about EDI information and diversity data may suggest institutional immaturity in addressing inequality or indicate that EDI implementation faces greater obstacles and slower progress.
We analyzed 9,000+ funded and rejected biomedical grant proposals from NIH and Novo Nordisk Foundation to examine the link between promotional language and grant success. Grants with more promotional words have higher funding odds. Younger, male, and highly cited PIs use more promotional language.
Long abstract
Grant proposals play a critical role in advancing medical science, yet little is known about how language influences funding success. This study analyzes over 9,000 biomedical grant proposals from the NIH and Novo Nordisk Foundation (NNF), including both funded and rejected applications, to investigate the relationship between promotional language and grant success. Using a validated lexicon of 139 promotional words, we find that grants containing a higher percentage of promotional language are significantly more likely to be funded. Specifically, an increase in promotional wording raises the odds of funding by up to 60%, even after controlling for factors such as a principal investigator’s (PI) prior grant success, publication impact, and proposal characteristics. Additionally, we examine who uses promotional language and find that younger PIs, male PIs, and those applying for larger grants tend to use more promotional words. While the use of promotional language may reflect confidence in an idea’s importance, it also raises questions about whether such language enhances or distorts the review process. Future research should explore the causal mechanisms linking promotional language and funding outcomes, including its potential influence on reviewer perception and recall. Understanding the role of language in funding decisions is crucial for promoting fairness and transparency in grant evaluations. These findings contribute to broader discussions on science communication, innovation, and equity in biomedical research funding.
This study analyzes the relationship between funding patterns at both the agency and project levels, and research performance—measured by impact, innovation, and goal achievement—in the context of mission-oriented basic research in China.
Long abstract
As an increasing amount of research funding is directed towards mission-oriented basic research, the concentration versus dispersion of funding has become a critical issue. This is particularly salient for mission-oriented basic research within the context of China's evolving funding landscape.
Drawing on China's landmark 15-year science and technology plan, the National Medium- and Long-Term Program for Science and Technology Development (MLP 2006-2020), this study first identifies the government's designated basic research priorities. We then match these priorities with top-down projects funded by different agencies. Based on this dataset, we measure funding concentration for each priority at both the agency and project levels. Furthermore, we assess three tiers of performance metrics: research impact, innovation (encompassing novelty and disruptiveness), and goal achievement (specifically, the attainment of macro-level innovation goals outlined in the MLP).
Our results reveal that project-level funding concentration promotes all three performance metrics. In contrast, while agency-level concentration has a positive effect on research impact and innovation, it negatively affects goal achievement. These findings provide evidence-based insights for optimizing funding mechanisms for mission-oriented basic research.
Using agent-based modelling, we show that competitive funding schemes paradoxically undermine long-term data sharing adoption. Neither large competitive grants nor small distributed funding alone can drive sustainable change without addressing the underlying costs of data sharing practices.
Long abstract
Policy makers increasingly mandate data sharing practices, yet we lack systematic evidence about the effectiveness of different implementation approaches. Using an agent-based model, we examine how funding schemes and incentive structures affect the uptake of data sharing practices among competing research teams.
Our simulations reveal a paradoxical relationship between competitive funding and data sharing: while highly competitive funding schemes with large grants can accelerate initial adoption, they lead to lower sharing rates in the long term. This occurs because the uncertainty associated with competitive funding negatively affects the cost-benefit ratio of data sharing for most teams. Conversely, more distributive funding schemes with smaller grants fail to provide teams with sufficient resources to absorb data sharing costs, also limiting uptake.
We find that without adequate support infrastructure to minimize costs, funding agencies alone are unlikely to drive sustainable adoption of data sharing practices.
The community structure of scientific fields further complicates this dynamic, with network effects generally dampening sharing rates compared to unconnected scenarios. Our findings suggest that attempts to reform reward systems toward open science principles must carefully consider the complex interplay between funding structures, incentives, and researchers' strategic adaptations.
In this talk, we examine in detail the critical roles of data sharing costs and cumulative advantage effects, with particular attention to how these factors can negatively impact sharing adoption. We conclude by critically examining how simulation approaches can contribute to evidence-based policy implementation in scholarly communication reform.
Targeted research funding aims to address societal challenges or needs. We study how targeted funding programmes shift the research landscape. Based on data from SNSF, RCN and NNF combined with Dimensions, we use a high-resolution topic clustering model to compare pre- and post-award publications.
Long abstract
We compare targeted and non-targeted funding programmes to try to understand how targeted research funding shifts the research landscape.
Our analysis is based on data collected from the Swiss National Science Foundation (SNSF), Research Council Norway (RCN) and Novo Nordisk Foundation (NNF), combined with grants and publications data from Dimensions. The collected data spans 100 different targeted funding programmes, covering over 10,000 grants, and spans 70 different non-targeted funding programmes, covering over 80,000 grants. For each grant, we collected publications from the PI, from both before the grant and after the grant. Each publication is assigned to a scientific topic on the basis of a clustering method of the entire citation network of Dimensions.
We study the difference between the propensity to publish in a certain topic before a grant was awarded and the propensity to publish in that topic after the grant was awarded. Due to sparsity, we regularise the calculation of these differences using weakly informative Bayesian priors. The scientific landscape is dynamic and shows endogenous changes, also in the absence of targeted research funding. We therefore compare these differences to baseline rates of change for non-targeted research funding. We aggregate these differences across topics and funding programmes to analyse whether targeted funding programmes show larger changes in the research landscape than non-targeted funding programmes.
We have now collected most data. Initial results suggest there is a close alignment between publishing practices and targeted research funding. We expect to present full results at the conference.
Short Abstract
This session will hear findings from six recent studies of different aspects of research funding systems. Topics will include: incentives and accountabilities for data sharing; use of promotional language in proposals; large-scale thematic funding; and research funding landscape analysis.
Long Abstract
Money talks, and when it does it influences many of the things that researchers do and say. This session comprises six papers looking at different aspects of the funder-researcher interaction. Anna Catharina Vieira Armond explores the challenges different funders face in formulating consistent requirements for data management and sharing plans, while Thomas Klebel examines how the complex interplay between funding structures, incentives, and researchers' strategic adaptations may ultimately inhibit data sharing behaviours.
Problems with a lack of consistency are also apparent from an examination of the collection and use of EDI data by funding agencies. Yohanna Juk discusses how a lack of clear communication likely frustrates efforts to create a more diverse and inclusive academy.
Turning to the question of the influence funders on research, Aruhan Bai presents results from a which found that a large grant scheme in China enhanced the subsequent funding and citation rates of funded researchers, but was curiously associated with lower disruption indices. In the same territory, Emer Brady discusses the results of an ongoing investigation of how targeted (as opposed to non-targeted) funding shifts research activity.
And finally, Huilian Sophie Qiu looks at the impact of researchers on funders. Her paper reports that the use of promotional language in grant applications is associated with substantially higher odds of winning funding and asks: is such language warranted or does it sustain biases within the research community?
Accepted papers
Session 1 Monday 30 June, 2025, -