Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty
Nate Breznau, Eike Mark Rinke, Alexander Wuttke, Hung Hoang Viet Nguyen, Muna Adem, Jule Adriaans, Amalia Álvarez-Benjumea, Henrik Kenneth Andersen, Daniel Auer, Flávio Azevedo, Oke Bahnsen, Dave Balzer, Gerrit Bauer, Paul Cornelius Bauer, Markus Baumann, Sharon Baute, Verena Benoit, Julian Bernauer, Carl Berning, Anna Berthold, Felix S. Bethke, Thomas Biegert, Katharina Blinzler, Johannes N. Blumenberg, Licia Bobzien, Andrea Bohman, Thijs Bol, Amie Bostic, Zuzanna Brzozowska, Katharina Burgdorf, Klaus Burger, Kathrin Busch, Juan Carlos Castillo, Nathan Chan, Pablo Christmann, Roxanne Connelly, Christian S. Czymara, Elena Damian, Alejandro Ecker, Achim Edelmann, Maureen A. Eger, Simon Ellerbrock, Anna Forke, Andrea Förster, Chris Gaasendam, Konstantin Gavras, Vernon Gayle, Theresa Gessler, Timo Gnambs, Amélie Godefroidt, Max Grömping, Martin Groß, Stefan Gruber, Tobias Gummer, Andreas Hadjar, Jan Paul Heisig, Sebastian Hellmeier, Stefanie Heyne, Magdalena Hirsch, Mikael Hjerm, Oshrat Hochman, Andreas Hövermann, Sophia Hunger, Christian Hunkler, Nora Huth-Stöckle, Zsófia S. Ignácz, Laura Jacobs, Jannes Jacobsen, Bastian Jaeger, Sebastian Jungkunz, Nils Jungmann, Mathias Kauff, Manuel Kleinert, Julia Klinger, Jan-Philipp Kolb, Marta Kołczyńska, John Kuk, Katharina Kunißen, Dafina Kurti Sinatra, Alexander Langenkamp, Philipp M. Lersch, Lea-Maria Löbel, Philipp Lutscher, Matthias Mader, Joan E. Madia, Natalia Malancu, Luis Maldonado, Helge Marahrens, Nicole Martin, Paul Martinez, Jochen Mayerl, Oscar J. Mayorga, Patricia McManus, Kyle McWagner, Cecil Meeusen, Daniel Meierrieks, Jonathan Mellon, Friedolin Merhout, Samuel Merk, Daniel Meyer, Leticia Micheli, Jonathan Mijs, Cristóbal Moya, Marcel Neunhoeffer, Daniel Nüst, Olav Nygård, Fabian Ochsenfeld, Gunnar Otte, Anna Pechenkina, Christopher Prosser, Louis Raes, Kevin Ralston, Miguel R. Ramos, Arne Roets, Jonathan Rogers, Guido Ropers, Robin Samuel, Gregor Sand, Ariela Schachter, Merlin Schaeffer, David Schieferdecker, Elmar Schlueter, Regine Schmidt, Katja Schmidt, Alexander Schmidt‐Catran, Claudia Schmiedeberg, Jürgen Schneider, Martijn Schoonvelde, Julia Schulte-Cloos, Sandy Schumann, Reinhard Schunck, Jürgen Schupp, Julian Seuring, Henning Silber, Willem W. A. Sleegers, Nico Sonntag, Alexander Staudt, Nadia Steiber, Nils D. Steiner, Sebastian Sternberg, Dieter Stiers, Dragana Stojmenovska, Nora Storz, Erich Striessnig, Anne-Kathrin Stroppe, Janna Teltemann, Andrey Tibajev, Brian Tung, Giacomo Vagni, Jasper Van Assche, Meta van der Linden, Jolanda van der Noll, Arno Van Hootegem, Stefan Vogtenhuber, Bogdan Voicu, Fieke M. A. Wagemans, Nadja Wehl, Hannah Werner, Brenton M. Wiernik, Fabian Winter, Christof Wolf, Yuki Yamada, Nan Zhang, Conrad Ziller, Stefan Zins, Tomasz Żółtak
Proceedings of the National Academy of Sciences · 2022 · 인용 225
This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis.
We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes.
More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested.
These results call for greater epistemic humility and clarity in reporting scientific findings.