The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Public use and public funding of science
Open accessAbstract
Knowledge of how science is consumed in public domains is essential for understanding the role of science in human society. Here we examine public use and public funding of science by linking tens of millions of scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains—government documents, news media and marketplace invention. We find that different public domains draw from various scientific fields in specialized ways, showing diverse patterns of use. Yet, amidst these differences, we find two important forms of alignment. First, we find universal alignment between what the public consumes and what is highly impactful within science. Second, a field’s public funding is strikingly aligned with the field’s collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet, collectively, science and society interface with remarkable alignment between scientific use, public use and funding. Studying production, funding and consumption of science, the authors find a strong alignment between what the public consumes and what is impactful, as well as an alignment between funding and collective public use.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Through competitive grant programs at agencies such as the NSF and the NIH, decisions about the allocation of taxpayer dollars influence which scientific ideas receive support, which fields advance, and which investigators are able to initiate and sustain research programs (3–10).”
From The rise of large language models and the direction and impact of US federal research funding (2026) · cites this paper as [7]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Thus, the federal funding process plays a central role in shaping the direction, diversity, and long-run impact of the US scientific enterprise and—given America’s scientific leadership—the global research landscape as well (3–10).”
From The rise of large language models and the direction and impact of US federal research funding (2026) · cites this paper as [7]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Economic Welfare and the Allocation of Resources for Invention
Arrow, K. J. (1962) · Princeton University Press eBooks · doi:10.1515/9781400879762-024 · Cited by 8,891
Etzkowitz, H., & Loet Leydesdorff, A. (2000) · Research Policy · doi:10.1016/s0048-7333(99)00055-4 · Cited by 8,632
Double-slit photoelectron interference in strong-field ionization of the neon dimer
Kunitski, M., Eicke, N., Huber, P., Köhler, J., Zeller, S., Voigtsberger, J., Schlott, N., Henrichs, K., Sann, H., Trinter, F., et al. (2019) · Institutional Repository of Leibniz Universität Hannover (Leibniz Universität Hannover) · doi:10.15488/5174 · Cited by 8,378
Double-slit photoelectron interference in strong-field ionization of the neon dimer
Kunitski, M., Eicke, N., Huber, P., Köhler, J., Zeller, S., Voigtsberger, J., Schlott, N., Henrichs, K., Sann, H., Trinter, F., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-07882-8 · Cited by 8,162
The Increasing Dominance of Teams in Production of Knowledge
Wuchty, S., Jones, B. F., & Uzzi, B. (2007) · Science · doi:10.1126/science.1136099 · Cited by 3,615
Self-citationPrice, D. J. D. S. (1965) · Science · doi:10.1126/science.149.3683.510 · Cited by 3,205
The Many Meanings of Research Utilization
Weiss, C. H. (1979) · Public Administration Review · doi:10.2307/3109916 · Cited by 2,364
Rising Above The Gathering Storm: Energizing and Employing America for a Brighter Economic Future
Augustine, N. R. (2006) · Cited by 2,064
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
Self-citationOn the sources and significance of interindustry differences in technological opportunities
Klevorick, A. K., Levin, R. C., Nelson, R. R., & Winter, S. G. (1995) · Research Policy · doi:10.1016/0048-7333(93)00762-i · Cited by 1,405
Research works printed but not linked: 8
- Merton, R. K. The Sociology of Science: Theoretical and Empirical Investigations (Univ. of Chicago Press, 1973).
- Mokyr, J. The Gifts of Athena: Historical Origins of the Knowledge Economy (Princeton Univ. Press, 2002).
- Stephan, P. E. The economics of science. J. Econ. Lit. 34, 1199–1235 (1996).
- Landau, R., Rosenberg, N. & National Academy of Engineering. The Positive Sum Strategy: Harnessing Technology for Economic Growth (National Academies Press, 1986).
- National Research Council. Knowledge and Policy: The Uncertain Connection (The National Academies Press, 1978).
- National Research Council. Using Science as Evidence in Public Policy (National Academies Press, 2012).
- Hatfield, E. Proxmire’s golden fleece award. Relationship Research News 4, 5–9 (2006).
- Garfield, E. & Merton, R. K. Citation Indexing: Its Theory and Application in Science, Technology, and Humanities. Vol. 8 (Wiley New York, 1979).
Cited by
Sorted by citations
Gender-diverse teams produce more novel and higher-impact scientific ideas
Yang, Y., Tian, T. Y., Woodruff, T. K., Jones, B. F., & Uzzi, B. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2200841119 · Cited by 361
“In this research we focused on medicine, a large branch of science and among the most funded with its wide array of downstream applications (3, 60).”
BackgroundSelf-citationSciSciNet: A large-scale open data lake for the science of science research
Lin, Z., Yin, Y., Liu, L., & Wang, D. (2023) · Scientific Data · doi:10.1038/s41597-023-02198-9 · Cited by 157
“relationships among scientific publications, there has been growing interest in studying how science interacts with other socioeconomic institutions 35,36,41,55,81,82 .”
BackgroundResultInfluentialSelf-citationData, measurement and empirical methods in the science of science
Liu, L., Jones, B. F., Uzzi, B., & Wang, D. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01562-4 · Cited by 143
“Policy documents 67,68 help us to understand the role of science in the halls of government 69 and policy making 12,68 .”
BackgroundSelf-citationQuantifying the use and potential benefits of artificial intelligence in scientific research
Gao, J., & Wang, D. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02020-5 · Cited by 81
“Given that tomorrow’s technological developments often begin upstream from basic scientific research 128–130 , a more robust understanding of the impact of AI on science may further inform a range of important policy considerations for the future of education, research and innovation 2–4 .”
Self-citationBreaking Out of the Ivory Tower: A Large-scale Analysis of Patent Citations to HCI Research
Cao, H., Lu, Y., Deng, Y., McFarland, D. A., & Bernstein, M. S. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581108 · Cited by 63
“To fill this gap, we draw on methods from the growing measurement literature on innovation in translational sciences [1, 7, 45, 50, 77], where patent citations to research have been regarded as a valuable proxy of the impact that science has on industrial practice.”
MethodRehman, O. A., Borri, E., Palomba, V., Frazzica, A., Brancato, V., Botargues, T., & Cabeza, L. F. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.112795 · Cited by 30
Global distribution of research efforts, disease burden, and impact of US public funding withdrawal
Schmallenbach, L., Bley, M., Bärnighausen, T., Sugimoto, C. R., Lerchenmüller, C., & Lerchenmueller, M. (2025) · Nature Medicine · doi:10.1038/s41591-025-03923-0 · Cited by 33
“As such, science requires public funding 11,12 ; the social contract underlying the rationale of this funding is that the research is responsive to societal needs 13,14 .”
Fueling the fire? How government support drives technological progress and complexity
Nast, C., Broekel, T., & Entner, D. (2024) · Research Policy · doi:10.1016/j.respol.2024.105005 · Cited by 27
Rescaling the disruption index reveals the universality of disruption distributions in science
Yang, A. J., Gong, H., Wang, Y., Zhang, C., & Deng, S. (2023) · Scientometrics · doi:10.1007/s11192-023-04889-x · Cited by 29
“The realm of science is a multifaceted and intricate domain, characterized by its intrinsic complexity and vast interconnections (Myers, 2020; Price, 1965; Wang & Barabási, 2021; Wang et al., 2013; Yin et al., 2022).”
Are disruptive papers more likely to impact technology and society?
Yang, A. J., Yan, X., Hu, H., Hu, H., Kong, J., & Deng, S. (2024) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24947 · Cited by 24
“…the availability of diverse datasets, such as patent citations (Ahmadpoor & Jones, 2017), clinical trials (Azoulay et al., 2019), news sources (Yin et al., 2022), and social media metrics (Costas et al., 2021; Sugimoto et al., 2017), has allowed certain scientific endeavors to transcend…”
InfluentialUnveiling the impact and dual innovation of funded research
Yang, A. J. (2023) · Journal of Informetrics · doi:10.1016/j.joi.2023.101480 · Cited by 23
SciSciGPT: advancing human–AI collaboration in the science of science
Shao, E., Wang, Y., Qian, Y., Pan, Z., Liu, H., & Wang, D. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00906-6 · Cited by 26
Self-citationInfluence of research on open science in the public policy sphere
Filippo, D. D., & Sastrón-Toledo, P. (2023) · Scientometrics · doi:10.1007/s11192-023-04645-1 · Cited by 19
Nagaraj, A., & Tranchero, M. (2023) · National Bureau of Economic Research · doi:10.3386/w31372 · Cited by 17
Consistent effects of science and scientist characteristics on public trust across political regimes
Younger-Khan, S., Weidmann, N. B., & Oswald, L. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03909-2 · Cited by 20
“High-impact research sees greater public consumption, and this public use drives greater funding towards high-impact research areas (Yin et al., 2022).”
Science of science: A multidisciplinary field studying science
Krauß, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e36066 · Cited by 29
“We can foster science through economies of scale, a reward system, science policy and targeted funding [25 – 28, 40, 100 ].”
The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study
Zhang, Y., Jin, B., Zhu, Q., Yu, M., & Han, J. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543507.3583354 · Cited by 14
Gross, K., & Bergstrom, C. T. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002750 · Cited by 13
“— from the public to support the scientific endeavor in exchange for the knowledge that the community produces [10].”
BackgroundInfluentialNovak, B. J., Brand, S., Phelan, R., Plichta, S., Ryder, O., & Wiese, R. (2025) · Animals · doi:10.3390/ani15070989 · Cited by 15
Unraveling topic switching and innovation in science
Yang, A. J. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104171 · Cited by 18
Mahfouz, B., Capra, L., & Mulgan, G. (2024) · Sustainable Development · doi:10.1002/sd.3214 · Cited by 12
“Early studies have explored how frequently scholarly research is cited in policy, using academic disciplines as a framework for comparing between different fields (Haunschild & Bornmann, 2017; Fang et al., 2020; Yin et al., 2022).”
Taniguchi, T., Takagi, S., Otsuka, J., Hayashi, Y., & Hamada, H. T. (2025) · Royal Society Open Science · doi:10.1098/rsos.241678 · Cited by 19
“Modelling such target selection process, as mentioned above, could provide deeper insights into the effect of the society to science.”
Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding
Zhang, Y., Cheng, H., Shen, Z., Liu, X., Wang, Y., & Gao, J. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.820 · Cited by 13
The role of preprints in open science: Accelerating knowledge transfer from science to technology
Wang, Z., Chen, Y., & Yang, C. (2025) · Journal of Informetrics · doi:10.1016/j.joi.2025.101663 · Cited by 13
“…to as scientific non-patent references (SNPRs) – more directly captures the knowledge transfer from basic scientific research to technological innovation, a critical precursor to commercial products (Cao et al., 2023; Higham et al., 2021; Li et al., 2014; Munari et al., 2022; Yin et al., 2022).”
How to detect the sleeping beauty papers and princes in technology considering indirect citations?
Feng, S., Li, H., & Qi, Y. (2023) · Journal of Informetrics · doi:10.1016/j.joi.2023.101431 · Cited by 9
Review: technological resources for vulnerable communities
Bosquet, F. J. S., Carreño, L., & Giorgi, E. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102354 · Cited by 8
The k-step h-index in citation networks at the paper, author, and institution levels
Yang, A. J., Wu, L., Zhang, Q., Wang, H., & Deng, S. (2023) · Journal of Informetrics · doi:10.1016/j.joi.2023.101456 · Cited by 10
O’Boyle, E. H., Götz, M., & Zivic, D. C. (2023) · Journal of Business and Psychology · doi:10.1007/s10869-023-09890-y · Cited by 9
“It is well-established that research tends to follow the money (e.g., Fabbri et al., 2018; Santos & Horta, 2018; Yin et al., 2022).”
BackgroundThe dynamics of issue attention in policy process scholarship
Fagan, E. J., Furnas, A. C., Koski, C. J., Thomas, H. F., Workman, S., & Connor, C. (2024) · Policy Studies Journal · doi:10.1111/psj.12548 · Cited by 7
A 13‐step framework for better integration of streamlined conservation research
Borzée, A. (2023) · Integrative Conservation · doi:10.1002/inc3.28 · Cited by 6
“Greater awareness and concern from the general population not only acknowledges the existence of a problem but also increases the likelihood of obtaining research grants to solve the issue (Yin et al., 2022).”
BackgroundFemale-led teams produce more innovative ideas yet receive less scientific impact
Yang, A. J., Ding, Y., & Liu, M. (2024) · Quantitative Science Studies · doi:10.1162/qss_a_00335 · Cited by 10
Krauß, A. (2024) · doi:10.1093/9780198937401.001.0001 · Cited by 7
The rise of large language models and the direction and impact of US federal research funding
Qian, Y., Wen, Z., Furnas, A. C., Bai, Y., Shao, E., & Wang, D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2601439123 · Cited by 5
Self-citationUncovering drivers of climate research in policy with pretrained language models
Mahfouz, B., Capra, L., & Mulgan, G. (2025) · Patterns · doi:10.1016/j.patter.2025.101342 · Cited by 5
Wang, Y., Qian, Y., Qi, X., Cao, N., & Wang, D. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3327387 · Cited by 8
Self-citationTripodi, G., Lillo, F., Mavilia, R., Mina, A., Chiaromonte, F., & Lamperti, F. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad7479 · Cited by 4
“However, we move beyond citations in the scientific domain to incorporate knowledge flows to technological innovations (i.e. patents) and to the policy and public discourse (i.e. policy documents and media outlets) [ 30–32].”
Earth Science Education #7. GeoTrails: Accessible Online Tools for Outreach and Education
Maloney, K. M., Peace, A. L., Hansen, J., Hum, K. L., Nielsen, J. P., Pearson, K., Ramharrack-Maharaj, S., Schwarz, D. M., Papangelakis, E., & Eyles, C. H. (2023) · Geoscience Canada · doi:10.12789/geocanj.2023.50.198 · Cited by 4
Wrightson, J. G., Lasinsky, A. M., Snell, R. R., Hogel, M., Mota, A., Khan, K. M., & Ardern, C. L. (2024) · medRxiv · doi:10.1101/2024.05.29.24308137 · Cited by 4
“66 67 Biomedical science and its benefits to society depend on successful applications for public research funding [15] .”
Wang, Z., Lu, Y., Zhou, Y., & Ji, J. (2024) · Journal of Informetrics · doi:10.1016/j.joi.2024.101562 · Cited by 3
Yuan, X., Chen, X., Mao, J., & Li, G. (2025) · Scientometrics · doi:10.1007/s11192-025-05280-8 · Cited by 3
Wang, J., Cai, S., & Xie, Q. (2025) · Asia Pacific Journal of Management · doi:10.1007/s10490-025-10062-0 · Cited by 3
“On the other hand, government subsidies play a critical role in addressing financial constraints and encouraging firms to engage in joint initiatives (Yin et al., 2022).”
Regression discontinuity design and its applications to Science of Science: A survey
Li, M., Zhang, Y., & Wang, Y. (2023) · Journal of Data and Information Science · doi:10.2478/jdis-2023-0008 · Cited by 3
“Researchers mainly focus on understanding correlational behaviors embedded in such datasets (AlShebli et al., 2018), or studying the underlying regularities in descriptive natures (Yin et al., 2022).”
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0013 · Cited by 3
Professors in the media: dynamics of cumulative advantage, reputation, and gender
Heiberger, R. H., Hofstra, B., & Unger, S. (2025) · European Sociological Review · doi:10.1093/esr/jcaf037 · Cited by 2
COVID-19 education policy often relied on older research despite available new evidence
Mahfouz, B., Capra, L., & Mulgan, G. (2026) · STAR Protocols · doi:10.1016/j.xpro.2026.104710 · Cited by 2
“10,11 A key limitation underlies much of this quantitative evidence.”
Benz, P., & Rossier, T. (2023) · Revue d anthropologie des connaissances · doi:10.4000/rac.30065 · Cited by 2
Big Science, Innovation, and Societal Contributions
Liyanage, S., Nordberg, M., & Streit-Bianchi, M. (2024) · doi:10.1093/oso/9780198881193.001.0001 · Cited by 1
Big Science and Social Responsibility of the Digital World
Wink, R., Meglio, A. D., Streit-Bianchi, M., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0012 · Cited by 1
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0009 · Cited by 1
Science of Science: An Integrated and Methods-Driven Understanding of Science
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0017 · Cited by 1
Wrightson, J. G., Lasinsky, A. M., Snell, R. R., Hogel, M., Mota, A., Khan, K. M., & Ardern, C. L. (2025) · FACETS · doi:10.1139/facets-2024-0116 · Cited by 1
Roessger, K. M., & Greenleaf, A. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1556464 · Cited by 2
Cruz, C. H. B. (2022) · Revista USP · doi:10.11606/issn.2316-9036.i135p71-100 · Cited by 1
Big Science Medical Applications from Accelerator Physics
Safavi‐Naeini, M., Boyle, T. P., Sheehy, S., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0010 · Cited by 1
The Evolution of Astrophysics towards Big Science
Reitze, D. H., Duffy, A. R., Gilbert, J., Casali, M. M., Barberio, E. L., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0009 · Cited by 1
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0001 · Cited by 1
Li, X., Wu, C., & Zhang, J. (2025) · Review of Policy Research · doi:10.1111/ropr.70006 · Cited by 1
Ruff, E. O., Bradshaw, L. M., & Lester, S. E. (2025) · Reviews in Aquaculture · doi:10.1111/raq.70079 · Cited by 1
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0005 · Cited by 1
Nagaraj, A., & Tranchero, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4483672 · Cited by 1
Uncovering Drivers of Science Use in Climate Policy with Pretrained Language ModelsPreprint
Mahfouz, B., Capra, L., & Mulgan, G. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5197403 · Cited by 1
Gender-Specific FavoritismPreprint
Huang, D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4291597
Gender-Specific FavoritismPreprint
Huang, D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4279002
Шевчук, О. (2022) · Aktual’ni problemi pravoznavstva · doi:10.35774/app2022.04.102
Lu, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4420484
Science of Public Recognition and Benefits (Sprb): Team, Impact, Novelty, and DisruptionPreprint
Yang, A. J., & Deng, S. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4478791
The entrepreneurial revolution in science research and education
Halma, M. T. J. (2024) · Scientific Bulletin of Mukachevo State University Series “Pedagogy and Psychology” · doi:10.52534/msu-pp1.2024.46
The Determinants of Science-Based Green PatentsPreprint
Nutarelli, F., Corrocher, N., & Morrison, A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4838427
The Future of Big Science and Social Impacts
Liyanage, S. I. H., Nordberg, M., & Streit-Bianchi, M. (2024) · doi:10.1093/oso/9780198881193.003.0016
Liyanage, S. I. H., Nordberg, M., & Streit-Bianchi, M. (2024) · doi:10.1093/oso/9780198881193.002.0012
Big Science, Leadership and Collaboration
McCarthy, G., Manset, D., Streit-Bianchi, M., Skvarciany, V., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0008
Thong, C., Kocsis, A., Canals, A., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0007
Future of Big Science Projects in Particle Physics
Taylor, G., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0014
A Machine with Endless Frontiers
Evans, L., Bordry, F., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0004
Benedikt, M., Ellis, J. R., Charitos, P., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0006
Well-ordered Big Science, Innovation, and Social Entrepreneurship
Shah, F., Bressan, B., Tello, P. G., Streit-Bianchi, M., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0013
Innovating Accelerator Technologies for Society
Ballarino, A., Boyle, T. P., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0005
Big Science as a Complex Human Enterprise
Bressan, B., Kocsis, A., Tello, P. G., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0011
Big Science and Society as Seen through Research Lenses
Nordberg, M., Liyanage, S. I. H., & Streit-Bianchi, M. (2024) · doi:10.1093/oso/9780198881193.003.0002
Jenni, P., Virdee, T. S., Pontecorvo, L., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0003
Liyanage, S. I. H., Nordberg, M., & Streit-Bianchi, M. (2024) · doi:10.1093/oso/9780198881193.003.0001
The Social and Educational Responsibility of Big Science
Goldfarb, S., Kourkoumelis, C., Skvarciany, V., Thong, C., & Liyanage, S. I. H. (2024) · doi:10.1093/oso/9780198881193.003.0015
Using Peer Review to Evaluate the Societal Relevance of Humanities ResearchPreprint
Conix, S., Vignero, L., Lemeire, O., Chi, P., & Li, L. (2024) · doi:10.31235/osf.io/cerfb
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0010
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0003
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0007
The Limits of Science: Grounded in the Boundaries of Our Methods and Mind
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0020
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0015 · Cited by 1
Science of Science: An Integrated Field Grounded in the New-Methods-Drive-Science Theory
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0018
Statistics and Mathematics of Science
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0014
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.005.0001
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0016 · Cited by 1
The Limits of Science: Expanding the Limits by Expanding Our Methodological Toolbox
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0021
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0006
Krauß, A. (2024) · Oxford University Press eBooks · doi:10.1093/9780198937401.003.0002
Metadata
- Authors
- Yin, Y., Dong, Y., Wang, K., Wang, D., & Jones, B. F.
- Affiliations
- Northwestern University (US)
- Microsoft (United States) (US)
- Corresponding author
- Wang, Dashun
- Jones, Benjamin F.
- Venue
- Nature Human Behaviour
- Published
- 2022-07-07
- Volume
- 6
- Issue
- 10
- Pages
- 1344-1350
- ISSN
- 2397-3374 (ISSN-L)
- OpenAlex
- W4284704491
- Cited by
- 123
- References
- 48
- Citations by year
- 2026: 10 · 2025: 22 · 2024: 65 · 2023: 21 · 2022: 5
- FWCI
- 17.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Human Behaviour (publishedVersion, public-domain)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research
- National Science Foundation
- Alfred P. Sloan Foundation
- Peter G. Peterson Foundation
- Topics
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Research, Science, and Academia
- Social Sciences › Library and Information Sciences › Academic Publishing and Open Access
- Keywords
- research funding, scientific publications, government documents, news media, science-society interface
- MeSH terms
- Humans, Mass Media, Knowledge
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
