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In the early 2010s, a crisis of reproducibility rocked the field of psychology.
The scientific method in the science of machine learning, 2019
Jessica Zosa Forde and Michela Paganini · 1904
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Ego depletion: Is the active self a limited resource?
Roy F. Baumeister, Ellen Bratslavsky, Mark Muraven, and Dianne M. Tice · 1998
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HARKing: Hypothesizing after the results are known
Norbert L. Kerr · 1998
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“How does it work?” versus “What are the laws?”: Two conceptions of psychological explanation
Robert Cummins · 2000
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Circular analysis in systems neuroscience: The dangers of double dipping
Nikolaus Kriegeskorte, W. Kyle Simmons, Patrick S. Bellgowan, and Chris I. Baker · 2009
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Power posing: Brief nonverbal displays affect neuroendocrine levels and risk tolerance
Dana R. Carney, Amy J.C. Cuddy, and Andy J. Yap · 2010
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Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect
Daryl J. Bem · 2011
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False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant
Joseph P. Simmons, Leif D. Nelson, and Uri Simonsohn · 2011
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Measuring the prevalence of questionable research practices with incentives for truth telling
Leslie K. John, George Loewenstein, and Drazen Prelec · 2012
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A peculiar prevalence of p values just below .05
E. J. Masicampo and Daniel R. Lalande · 2012
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Scientific utopia: II. Restructuring incentives and practices to promote truth over publishability
Brian A. Nosek, Jeffrey R. Spies, and Matt Motyl · 2012
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Editors’ introduction to the special section on replicability in psychological science: A crisis of confidence?
Harold Pashler and Eric-Jan Wagenmakers · 2012
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An agenda for purely confirmatory research
Eric-Jan Wagenmakers, Ruud Wetzels, Denny Borsboom, Han L.J. van der Maas, and Rogier A. Kievit · 2012
Cited alongside, same era.
Theoretical amnesia., 2013
Denny Borsboom · 2013
Cited alongside, same era.
Registered reports: A new publishing initiative at Cortex
Christopher D. Chambers · 2013
Cited alongside, same era.
The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time
Andrew Gelman and Eric Loken · 2013
Cited alongside, same era.
Against storytelling of scientific results
Yarden Katz · 2013
Cited alongside, same era.
Investigating variation in replicability: A “Many Labs” replication project
Richard A. Klein, Kate A. Ratliff, Michelangelo Vianello, Reginald B. Adams, Štěpán Bahník, Michael J. Bernstein, Konrad Bocian, Mark J. Brandt, Beach Brooks, Claudia Chloe Brumbaugh, Zeynep Cemalcilar, Jesse Chandler, Winnee Cheong, William E. Davis, Thierry Devos, Matthew Eisner, Natalia Frankowska, David Furrow, Elisa Maria Galliani, Fred Hasselman, Joshua A. Hicks, James F. Hovermale, S. Jane Hunt, Jeffrey R. Huntsinger, Hans Ijzerman, Melissa Sue John, Jennifer A. Joy-Gaba, Heather Barry Kappes, Lacy E. Krueger, Jaime Kurtz, Carmel A. Levitan, Robyn K. Mallett, Wendy L. Morris, Anthony J. Nelson, Jason A. Nier, Grant Packard, Ronaldo Pilati, Abraham M. Rutchick, Kathleen Schmidt, Jeanine L. Skorinko, Robert Smith, Troy G. Steiner, Justin Storbeck, Lyn M. Van Swol, Donna Thompson, A. E. Van ’T Veer, Leigh Ann Vaughn, Marek Vranka, Aaron L. Wichman, Julie A. Woodzicka, and Brian A. Nosek · 2014
On the state of the art of evaluation in neural language models
Gábor Melis, Chris Dyer, and Phil Blunsom · 2018
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Winner’s curse? On pace, progress, and empirical rigor
D. Sculley, Jasper Snoek, Ali Rahimi, and Alex Wiltschko · 2018
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Open science challenges, benefits and tips in early career and beyond
Christopher Allen and David M.A. Mehler · 2019
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Unreproducible research is reproducible
Xavier Bouthillier, César Laurent, and Pascal Vincent · 2019
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Show your work: Improved reporting of experimental results
Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, and Noah A. Smith · 2019
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Troubling trends in machine learning scholarship
Zachary C. Lipton and Jacob Steinhardt · 2019
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Cited alongside, same era.
Badges to acknowledge open practices: A simple, low-cost, effective method for increasing transparency
Mallory C. Kidwell, Ljiljana B. Lazarević, Erica Baranski, Tom E. Hardwicke, Sarah Piechowski, Lina-Sophia Falkenberg, Curtis Kennett, Agnieszka Slowik, Carina Sonnleitner, Chelsey Hess-Holden, et al · 2016
Cited alongside, same era.
Increasing transparency through a multiverse analysis
Sara Steegen, Francis Tuerlinckx, Andrew Gelman, and Wolf Vanpaemel · 2016
Cited alongside, same era.
Reporting score distributions makes a difference: Performance study of LSTM-networks for sequence tagging
Nils Reimers and Iryna Gurevych · 2017
Cited alongside, same era.
What does research reproducibility mean?
Steven N. Goodman, Daniele Fanelli, and John P.A. Ioannidis · 2018
Cited alongside, same era.
State of the art: Reproducibility in artificial intelligence
Odd Erik Gundersen and Sigbjørn Kjensmo · 2018
Cited alongside, same era.
Deep reinforcement learning that matters
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, and David Meger · 2018
Cited alongside, same era.
Preregistration of modeling exercises may not be useful
Steven N. MacEachern and Trisha Van Zandt · 2019
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Addressing the theory crisis in psychology
Klaus Oberauer and Stephan Lewandowsky · 2019
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Improving reproducibility in machine learning research (a report from the NeurIPS 2019 reproducibility program)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence D’Alché-Buc, Emily Fox, and Hugo Larochelle · 2020
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The theory crisis in psychology: How to move forward
Markus I. Eronen and Laura F. Bringmann · 2021
Closest in time.
Arrested theory development: The misguided distinction between exploratory and confirmatory research
Aba Szollosi and Chris Donkin · 2021
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