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Science and scientific research activities, in addition to the involvement of the researchers, require resources like research infrastructure, materials and reagents, databases and computational tools, journal subscriptions and publication charges etc. In order to meet these requirements, researchers try to attract research funding from different funding sources, both intramural and extramural. Though some recent reports provide details of the amount of funding provided by different funding agencies in India, it is not known what quantum of research output resulted from such funding. This paper, therefore, attempts to quantify the research output produced with the funding provided by different funding agencies to Indian researchers. The major funding agencies that supported Indian research publications are identified and are further characterized in terms of being national or international, and public or private. The analytical results not only provide a quantitative estimate of funded research from India and the major funding agencies supporting the research, but also discusses the overall context of research funding in India, particularly in the context of upcoming operationaliza

Research funding allocation remains a critical bottleneck in scientific advancement, yet the review process for funding proposals lacks the transparency that has revolutionized academic paper peer review. Traditional funding agencies operate with closed review systems, limiting accountability and preventing systematic improvements. We present OpenProposal, a proof-of-concept web-based platform that explores how transparency principles from OpenReview might be adapted to research funding proposal evaluation. Built using modern web technologies including Next.js , React , and Prisma , OpenProposal demonstrates the technical feasibility of public reviews, author rebuttals, and transparent decision-making while attempting to protect sensitive information such as budgets. Our platform prototype addresses key limitations identified in current funding systems by providing mechanisms for community engagement, reviewer accountability, and potential data-driven insights into peer review processes. Through system design and implementation, we explore how transparent funding review could potentially enhance scientific integrity and improve research funding decisions, though empirical validatio

We present a reconstruction of UKRI's Gateway to Research (GtR) database that links funding opportunities to their resulting project proposals through panel meeting outcomes. Unlike existing work that focuses primarily on funded projects and their outcomes, we close the complete funding lifecycle by integrating three previously disconnected data sources: the GtR project database, UKRI funding opportunities, and competitive funding decision records across UKRI's research councils. We describe the technical challenges of data collection, including navigating inconsistent publication formats and restricted access to panel decisions. The resulting dataset enables a holistic interrogation of the entire funding process, from opportunity announcement to research outcomes. We release the database and associated code.

Funding acknowledgments in scholarly publications provide large-scale trace data on organizations that support scientific research. We present a dataset for linking global science funding organizations to research publications by systematically disambiguating unique funding acknowledgment strings extracted from publication metadata. Funder names are matched to standardized organizational identifiers using a multi-stage pipeline that combines lexical normalization, similarity-based clustering, rule-based matching, named entity recognition assistance, and manual validation. The resulting dataset links 1.9 million unique funder strings to canonical organization identifiers and records match types and unresolved cases to support transparency. Technical validation includes paper-level comparisons across bibliometric sources and manual verification against full-text acknowledgment sections, with reported recall and precision metrics. This dataset supports analyses of funding flows, institutional funding portfolios, regional representation, and concentration patterns in the global research system.

Economic stability and progress in modern technological societies depend on vigorous and independent public funding of science and engineering research. When peer review or funding decisions are perceived as politically directed, scientists, funding agencies, and the public react in coupled and conflicting ways. We an evolutionary game-theoretic model to analyze how perceived political interference in science funding affects the interrelated behaviors of scientists, funding agencies, and the public. The model simulates scientists choosing to refuse peer reviews and retaliate, agencies responding by adopting AI-assisted review and altering reviewer pay, and the public accepting or rejecting these AI systems. Through numerical simulations, five principal findings are identified: (1) Operational capacity and institutional legitimacy are governed by separate conditions and can fail independently. (2) Legitimacy of the process is bistable, meaning final states are determined by the public's acceptance of AI. (3) Since the career cost for researchers refusing to review is generally low, resistance/retaliation cascades can readily ignite, leading identical institutions to entirely opposit

Scientific knowledge advances through within-country and cross-border scientific activities and collaborations, influenced by funding and strength of research enterprise. Sudden declines in research funding, for example from Federal sources in the United States (US) 2024-25, adversely impact on scientific collaboration. How rapid declines in funding affect the science enterprise and the magnitude of impact need to be analysed. Past studies have modelled the global scientific system as complex collaborative networks of entities and studied its topology and dynamics. However, these studies have not undertaken compensation analysis to real-world shocks that have produced rapid declines in scientific research funding. In this study we examine the effect of the sharp declines in the US Federal funding on cancer science research enterprise globally. We model the cancer science ecosystem as a 5-layer multiplex network of collaborative linkages between 233 countries and territories in grants and clinical trial co-investigations, paper co-authorships, co-inventions and patent co-ownerships. We quantify information flow in the multiplex system through network efficiency. Proposing a framewor

Understanding the broad impact of science and science funding is critical to ensuring that science investments and policies align with societal needs. Existing research links science funding to the output of scientific publications but largely leaves out the downstream uses of science and the myriad ways in which investing in science may impact human society. As funders seek to allocate scarce funding resources across a complex research landscape, there is an urgent need for informative and transparent tools that allow for comprehensive assessments and visualization of the impact of funding. Here we present Funding the Frontier (FtF), a visual analysis system for researchers, funders, policymakers, university leaders, and the broad public to analyze multidimensional impacts of funding and make informed decisions regarding research investments and opportunities. The system is built on a massive data collection that connects 7M research grants to 140M scientific publications, 160M patents, 10.9M policy documents, 800K clinical trials, and 5.8M newsfeeds, with 1.8B citation linkages among these entities, systematically linking science funding to its downstream impacts. As such, Fundin

While founder backgrounds account for less than 4% of funding variation among Y Combinator startups, this suggests that other factors, such as industry trends and product innovation, may play a more significant role in funding outcomes. Using data on 4,323 YC companies from 2005-2024 merged with S&P Global funding data, I estimate OLS regressions with batch year fixed effects on a regression sample of 2,113 companies. The coefficient on prior FAANG work experience is -0.251, indicating approximately 22% less funding. However, this result is not robust, as it changes direction in further analyses, suggesting that FAANG experience may not be a reliable predictor of funding. The most robust finding is that startups within Y Combinator that consist of larger founding teams tend to raise more funding, with each additional co-founder associated with approximately 21% more capital raised. While observable credentials such as prior FAANG work experience and top-tier education explain minimal variation in funding, the size of the founding team emerges as a more consistent predictor, highlighting the importance of team dynamics in securing capital. Unobserved factors like industry and pr

Competitive grant funding is associated with high costs and a potential bias to favor conservative research. This comment proposes integrating editorial preregistration, in the form of registered reports, into grant peer review processes as a reform strategy. Linking funding decisions to in principle accepted study protocols would reduce reviewer burden, strengthen methodological rigor, and provide an institutional foundation for (more) replication, theory driven research, and high risk research. Our proposal also minimizes strategic proposal writing and ensures scholarly output through the publication of preregistered protocols, regardless of funding outcomes. Possible implementation models include direct coupling of journal acceptance with funding, co review mechanisms, voucher systems, and lotteries. While challenges remain in aligning journal and funding agency procedures, the integration of preregistration and funding offers a promising pathway toward a more transparent and efficient research ecosystem.

Open Source Software (OSS) forms a critical layer of contemporary digital infrastructure, yet remains largely overlooked by the institutions and societies that depend on it. Despite growing institutional interest, the causal impact of public funding on OSS project sustainability remains empirically unresolved. Existing literature is divided between econometric and socio-technical approaches with few attempts at causal identification. This work aims to bridge that divide by combining a Goal-Question-Metric framework with the Generalized Synthetic Control Method to estimate the causal effect of the Sovereign Tech Fund on OSS repository activity. Counterfactual trajectories are constructed from a matched donor pool of unfunded projects, enabling identification of what funded repositories would have looked like in the absence of intervention. The main results show that the funding has a significant positive effect on project velocity metrics: commits, pull requests --both merged and new ones--, and new issues. There is no significant effect on the number of releases, contributors or closed issues. This indicates that the STF funding mobilises existing development activity rather than e

Academic grant programs are widely used to motivate international research collaboration and boost scientific impact across borders. Among these, bi-national funding schemes -- pairing researchers from just two designated countries -- are common yet understudied compared with national and multinational funding. In this study, we explore whether bi-national programs are associated with new collaborations and lasting partnerships. To this end, we conducted an observational bibliometric case study of the German--Israeli Foundation (GIF), covering 642 grants, 2,386 researchers, and 52,847 publications. Our results show that GIF funding is associated with increased co-authorship behavior during, and even slightly before, the grant period, but it is rarely linked with long-lasting co-authorship patterns that persist once the funding concludes. By tracing co-authorship before, during, and after the funding period, clustering collaboration trajectories with temporally-aware K-means, and predicting cluster membership with ML models, we find that 45% of teams with no prior co-authored publications become active while funded, yet activity declines rapidly post-award; roughly one-third sustain

Artificial Intelligence for Social Good (AI4SG) is a growing area that explores AI's potential to address social issues, such as public health. Yet prior work has shown limited evidence of its tangible benefits for intended communities, and projects frequently face real-world deployment and sustainability challenges. While existing HCI literature on AI4SG initiatives primarily focuses on the mechanisms of funded projects and their outcomes, much less attention has been given to the upstream funding agendas that influence project approaches. In this work, we conducted a reflexive thematic analysis of 35 funding documents, representing about $410 million USD in total investments. We uncovered a spectrum of conceptual framings of AI4SG and the approaches that funding rhetoric promoted: from biasing towards technology capacities (more techno-centric) to emphasizing contextual understanding of the social problems at hand alongside technology capacities (more balanced). Drawing on our findings on how funding documents construct AI4SG, we offer recommendations for funders to embed more balanced approaches in future funding call designs. We further discuss implications for how the HCI comm

Funding acknowledgments are important objects of study in the context of science funding. This study uses a mixed-methods approach to analyze the funding acknowledgments found in 2.3 million scientific publications published between 2008 and 2021 by authors affiliated with research institutions located in the Middle Eastern and North Africa (MENA). The aim is to identify the major funders, assess their contribution to national scientific publications, and gain insights into the funding mechanism in relation to collaboration and publication. Publication data from the Web of Science is examined to provide key insights about funding activities. Saudi Arabia and Qatar lead the region, as about half of their publications include acknowledgments to funding sources. Most MENA countries exhibit strong linkages with foreign agencies, mainly due to a high level of international collaborations. The distinction between domestic and international publications reveals some differences in terms of funding structures. For instance, Turkey and Iran are dominated by one or two major funders whereas a few other countries like Saudi Arabia showcase multiple funders. Iran and Kuwait are examples of cou

To analyse the outcomes of the funding they provide, it is essential for funding agencies to be able to trace the publications resulting from their funding. We study the open availability of funding data in Crossref, focusing on funding data for publications that report research related to Covid-19. We also present a comparison with the funding data available in two proprietary bibliometric databases: Scopus and Web of Science. Our analysis reveals a limited coverage of funding data in Crossref. It also shows problems related to the quality of funding data, especially in Scopus. We offer recommendations for improving the open availability of funding data in Crossref.

In cryptocurrency markets, a key challenge for perpetual future issuers is maintaining alignment between the perpetual future price and target value. This study addresses this challenge by exploring the relationship between funding rates and perpetual future prices. Our results demonstrate that by appropriately designing funding rates, the perpetual future price can remain aligned with the target value. We develop replicating portfolios for perpetual futures, offering issuers an effective method to hedge their positions. Additionally, we provide path-dependent funding rates as a practical alternative and investigate the difference between the original and path-dependent funding rates. To achieve these results, our study employs path-dependent infinite-horizon BSDEs in conjunction with arbitrage pricing theory. Our main results are obtained by establishing the existence and uniqueness of solutions to these BSDEs and analyzing the large-time behavior of these solutions.

The Optimism Retroactive Project Funding (RetroPGF) is a key initiative within the blockchain ecosystem that retroactively rewards projects deemed valuable to the Ethereum and Optimism communities. Managed by the Optimism Collective, a decentralized autonomous organization (DAO), RetroPGF represents a large-scale experiment in decentralized governance. Funding rewards are distributed in OP tokens, the native digital currency of the ecosystem. As of this writing, four funding rounds have been completed, collectively allocating over 100M dollars, with an additional 1.3B dollars reserved for future rounds. However, we identify significant shortcomings in the current allocation system, underscoring the need for improved governance mechanisms given the scale of funds involved. Leveraging computational social choice techniques and insights from multiagent systems, we propose improvements to the voting process by recommending the adoption of a utilitarian moving phantoms mechanism. This mechanism, originally introduced by Freeman et al. in 2019, is designed to enhance social welfare (using the L1 norm) while satisfying strategyproofness -- two key properties aligned with the application's

This study explores funding, authorship patterns, and citation impact of articles funded by the Ministry of Education and Science of Ukraine (MESU), the National Academy of Sciences of Ukraine (NASU), and the National Research Foundation of Ukraine (NRFU). The analysis focuses on articles published in Scopus-indexed journals between 2020 and 2023. The findings show that the share of articles funded by these agencies increased from 8.6% in 2020-2021 to 11.9% in 2022-2023. Foreign co-funding as well as international co-authorship and co-affiliations are consistently associated with higher citation impact. In particular, foreign co-affiliations are associated with higher field-normalised citation impact (FNCI) for MESU-funded articles in 2022-2023, exceeding that of articles jointly funded by MESU and foreign agencies. NASU funding is associated with only modest differences in citation impact relative to unfunded articles. These effects are small and not consistently significant across authorship patterns and become less pronounced in 2022-2023, as the citation impact of unfunded articles partially converges with that of funded articles. While the results should be interpreted as aver

Governments are increasingly employing funding for open source software (OSS) development as a policy lever to support the security of software supply chains, digital sovereignty, economic growth, and national competitiveness in science and innovation, among others. However, the impacts of public funding on OSS development remain poorly understood, with a lack of consensus on how to meaningfully measure them. This gap hampers assessments of the return on public investment and impedes the optimisation of public-interest funding strategies. We address this gap with a toolkit of methodological considerations that may inform such measurements, drawing on prior work on OSS valuations and community health metrics by the Community Health Analytics Open Source Software (CHAOSS) project as well as our first-hand learnings as practitioners tasked with evaluating funding programmes by the Next Generation Internet initiative and the Sovereign Tech Agency. We discuss salient considerations, including the importance of accounting for funding objectives, project life stage and social structure, and regional and organisational cost factors. Next, we present a taxonomy of potential social, economic

Participatory budgeting (PB) has been widely adopted and has attracted significant research efforts; however, there is a lack of mechanisms for PB which elicit project interactions, such as substitution and complementarity, from voters. Also, the outcomes of PB in practice are subject to various minimum/maximum funding constraints on 'types' of projects. We propose a novel preference elicitation scheme for PB which allows voters to express how their utilities from projects within 'groups' interact. We consider preference aggregation done under minimum and maximum funding constraints on 'types' of projects, where a project can have multiple type labels as long as this classification can be defined by a 1-laminar structure (henceforth called 1-laminar funding constraints). Overall, we extend the Knapsack voting model of Goel et al. [26] in two ways - enriching the preference elicitation scheme to include project interactions and generalizing the preference aggregation scheme to include 1-laminar funding constraints. We show that the strategyproofness results of Goel et al. [26] for Knapsack voting continue to hold under 1-laminar funding constraints. Moreover, when the funding constr