Ending publication bias: A values-based approach to surface null and negative results

Stephen Curry, Eunice Mercado-Lara, Virginia Arechavala-Gomeza, C Glenn Begley, Christophe Bernard, René Bernard, Stefano Bertuzzi, Needhi Bhalla, Dawn Bowers, Samuel Brod, Christopher Chambers, Michael R Dougherty, Yensi Flores Bueso, Stefânia Forner, Alexandra LJ Freeman, Magali Haas, Darla P Henderson, Kanika Khanna, Rebecca Lawrence, Kif Liakath-Ali, Christine Liu, Neil Malhotra, José G Merino, Edward Miguel, Rachel Miles, Mary Munson, Shinichi Nakagawa, Robert Nobles, Joy Owango, Michel Tuan Pham, Gina Poe, Alexandra N Ramirez, Sarvenaz Sarabipour, Jill L Silverman, Laura N Smith, P Sriramarao, Paul W Sternberg, Geeta K Swamy, Malú Gámez Tansey, Gonzalo E Torres, Erick H Turner, Lauren von Klinggraeff and Frances Weis-Garcia

Department of Economics, Working Paper Series from Department of Economics, Institute for Business and Economic Research, UC Berkeley

Abstract: Sharing knowledge is a basic tenet of the scientific community, yet publication bias arising from the reluctance or inability to publish negative or null results remains a long-standing and deep-seated problem, albeit one that varies in severity between disciplines and study types. Recognizing that previous endeavors to address the issue have been fragmentary and largely unsuccessful, this Consensus View proposes concrete and concerted measures that major stakeholders can take to create and incentivize new pathways for publishing negative results. Funders, research institutions, publishers, learned societies, and the research community all have a role in making this an achievable norm that will buttress public trust in science.

Keywords: 30 Agricultural; Veterinary and Food Sciences (for-2020); 31 Biological Sciences (for-2020); 32 Biomedical and Clinical Sciences (for-2020); Publication Bias (mesh); Humans (mesh); Publishing (mesh); Information Dissemination (mesh); Humans (mesh); Information Dissemination (mesh); Publishing (mesh); Publication Bias (mesh); Publication Bias (mesh); Humans (mesh); Publishing (mesh); Information Dissemination (mesh); 06 Biological Sciences (for); 07 Agricultural and Veterinary Sciences (for); 11 Medical and Health Sciences (for); Developmental Biology (science-metrix); 30 Agricultural; veterinary and food sciences (for-2020); 31 Biological sciences (for-2020); 32 Biomedical and clinical sciences (for-2020) (search for similar items in EconPapers)
Date: 2025-01-01
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