• A mathematical theory of knowledge, bias, science and pseudoscience: an original attempt to unify meta-science, cognitive science and philosophy using notions of information theory.
• Innovating retractions to reward self-correction: a METRICS-sponsored project aimed at improving literature amendment policies.
• Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications, in collaboration with Elisabeth Bik, uBiome, Ferric Fang, University of Washington School of Medicine, Arturo Casadevall, Johns Hopkins Bloomberg School of Public Health, and Rodrigo Costas, Leiden University, NL.
• What difference a retraction makes!Assessing the potential impact of article retractions on meta-analytical estimates, in collaboration with David Moher, University of Ottawa, Canada.
• From countries to individuals : unravelling the causes of bias and misconduct with multilevel meta-meta-analysis 2013-2016, PI, in collaboration with John PA Ioannidis, Stanford University, funded by NIH/Office of Research Integrity, 165,000 USD/year
• Historical trends of scientists' "productivity", PI, in collaboration with Vincent Larivière, Université de Montréa, CA
• The integrity of self-retracting scientists, a qualitative research study in collaboration with Medard Hilhorst, of Erasmus MC, The Netherlands.
• No study’s perfect: A cross-disciplinary analysis of published errata, PI, work partially funded by the Committee On Publication Ethics (COPE), 5,000 GBP, conducted in collaboration with Vincent Larivière, Université de Montréal , and Rodrigo Costas Comesana, Leiden University.
• Is research in the United States more biased than in the UK? Partially funded by a Strategic Research Support Fund of the School of Social and Political Science, University of Edinburgh (700 GBP)
• Bias, misconduct and the Hierarchy of the Sciences: towards a unified science of scientific objectivity. 2010-2013, Leverhulme Early-Career Fellowship 78,000 GBP ca
• Quantifying objectivity in the natural and social sciences. 2008-2010, Marie Curie Intra-European fellowship, 160,000 euro ca.

Fanelli D (2019) A theory and methodology to quantify knowledge. Royal Society Open Science - doi.org/10.1098/rsos.181055

Fanelli D (2018) Is science really facing a reproducibility crisis, and do we need it to? PNAS –doi.org/10.1073/pnas.1708272114

Fanelli D, Costas R, Fang FC, Casadevall A, Bik EM (2018) Testing hypotheses on risk factors for scientific misconduct via matched-control analysis of papers containing problematic image duplications. Science and Engineering Ethics - doi.org/10.1007/s11948-018-0023-7

Fanelli D, Ioannidis JPA, Goodman SN (2018) Improving the integrity of published science: an expanded taxonomy of retractions and corrections. European Journal of Clinical Investigation – 10.1111/eci.12898

Fanelli D, Costas R, Fang FC, Casadevall A, Bik EM (2017). Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications. bioRxiv - doi.org/10.1101/126805

Fanelli D, Costas R, Ioannidis JPA (2017) Meta-assessment of bias in science. PNAS - 10.1073/pnas.1618569114

Hosseini M, Hilhorst M, de Beaufort I, Fanelli D (2017) Doing the Right Thing: A Qualitative Investigation of Retractions Due to Unintentional Error. Science and Engineering Ethics - 10.1007/s11948-017-9894-2

Goodman S, Fanelli D, Ioannidis JPA (2016) What does reproducibility mean? Science Translational Medicine - 10.1126/scitranslmed.aaf5027

Fanelli D (2016) Set up a 'self-retraction' system for honest errors. Nature - 10.1038/531415a

Fanelli D & V Larivière (2016) Scientists' individual publication rate has not increased in a century. PLoS ONE - 10.1371/journal.pone.0149504

McCrary J, Christensen G & Fanelli D (2016) Conservative Tests under Satisficing Models of Publication Bias. PLoS ONE -10.1371/journal.pone.0149590

Fanelli D & Larivière V (2015). Are scientists really publishing more? Proceedings of the15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey.

Ioannidis JPA, Fanelli D, Drake Dunne D, Goodman SN (2015). Meta-research: Evaluation and improvement of research methods and practices. PLoS Biology -DOI: 10.1371/journal.pbio.1002264

Fanelli D, Costas R and Larivière V (2015). Misconduct Policies, Academic Culture and Career Stage, Not Gender or Pressures to Publish, Affect Scientific Integrity. PLoS ONE - DOI:10.1371/journal.pone.0127556

Fanelli D (2015) We need more research on causes and consequences, as well as on solutions. Addiction - 10.1111/add.12772

Pupovac V & Fanelli D (2015) Scientists admitting to plagiarism: a meta-analysis of surveys. Science and Engineering Ethics - 10.1007/s11948-014-9600-6

Yu B & Fanelli D (2014) Classifying Negative Findings in Biomedical Publications. Proceedings of the BioNLP 2014, Workshop on Biomedical Natural Language Processing.

Fanelli D (2014) Publishing: rise in retractions is a signal of integrity. Nature - doi:10.1038/509033a

Fanelli D & Ioannidis JPA (2014) Re-analyses actually confirm that US studies may overestimate effect sizes in softer research. PNAS - DOI: 10.1073/pnas.1322565111

Fanelli D (2013) Why growing retractions are (mostly) a good sign. PLoS Medicine - DOI: 10.1371/journal.pmed.1001563

Fanelli D & Ioannidis JPA (2013) US studies may overestimate effect sizes in softer research. PNAS - DOI:10.1073/pnas.1302997110

Fanelli D & Glanzel W (2013) Bibliometric evidence for a Hierarchy of the Sciences. PLoS ONE - DOI:10.1371/journal.pone.0066938

Fanelli D (2013) Only reporting guidelines can save (soft) science. European Journal of Personality 27(2): 124

Fanelli D (2013) Redefine misconduct as distorted reporting. Nature - DOI:10.1038/494149a

Fanelli D (2013) Positive results receive more citations, but only in some disciplines. Scientometrics - DOI:10.1007/s11192-012-0757-y

Fanelli D (2012) Any publicity is better than none: newspaper coverage increases citations, in the UK more than in Italy. Scientometrics - DOI:10.1007/s11192-012-0925-0

Fanelli D (2012) Negative results are disappearing from most disciplines and countries. Scientometrics - DOI:10.1007/s11192-011-0494-7

Fanelli D (2010) Do pressures to publish increase scientists' bias? An empirical support from US states data. PLoS ONE - DOI:10.1371/journal.pone.0010271

Fanelli D (2010) "Positive" results increase down the Hierarchy of the Sciences. PLoS ONE - DOI:10.1371/journal.pone.0010068

Fanelli D (2009) How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS ONE - DOI:10.1371/journal.pone.0005738

Book chapters:

Fanelli D (in press) Is the narrative of a crisis empirically supported? In: Jussim L, Krosnik J eds. Research Integrity in the Behavioural Sciences. Oxford Univ. Press.

Fanelli D (2020) Institutional pressures to publish: what effects do we see?. in: Mario Biagioli & Alexandra Lippman eds. Gaming the Metrics. MIT press.

Fanelli D (2011) The black, the white and the grey areas - towards an international and interdisciplinary definition of scientific misconduct. Pp. 77-87 in: Nick Steneck & Tony Meyer eds. Promoting Research Integrity on a Global Basis. World Scientific press.

Policy reports:

EU Mutual Learning Exercise on Research integrity (2019) Author of Report 2 (Incentives) and 4 (Training and Education). with input from Research Integrity Officers of 14 EU countries. Prepared for the European Commission, Directorate-General for Research and Innovation.

Linee guida del CNR per l'integrità nella ricerca (2015) (CNR's Guidelines for Research Integrity) co-athored with Cinzia Caporale and input from the CNR Ethics Committee

Honesty, Accountability and Trust: Fostering Research Integrity in Canada (2010) co-authored with the Expert Panel on Research Integrity, Council of Canadian Academies

Fanelli D (2017) A mathematical theory of knowledge, science, bias and pseudoscience V3 PeerJ-Preprints - 10.7287/peerj.preprints.1968v3

Fanelli D, Costas R, Fang FC, Casadevall A, Bik EM (2017). Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications. bioRxiv - doi.org/10.1101/126805