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Shishir Shakya

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Articles

Access to Mental Health Care Services and Suicide Rates in the United States

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By Shishir Shakya, Agnitra RoyChoudhury
| Wiley Online Library Verified
Data Availability Statement The data and codes that support the findings of this study are openly available in Harvard Dataverse at https://doi.org/10.7910/DVN/I36EPF. Supporting Information Filename Description pam70110-supp-0001-SuppMat.pdf839.9 KB Data S1 References , and . 1995. “Split-Sample Instrumental Variables Estimates of the Return to Cchooling.” Journal of Business & Economic Statistics 13, no. 2: 225–235. , and . 2001.
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Investigating the reproducibility of the social and behavioural sciences

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By Olivia Miske, Anna Lou Abatayo, Mason Daley, Mirka Dirzo, Noah Haber, Krystal M. Hahn, Melissa Kline Struhl, Brinna Mawhinney, Priya Silverstein, Theresa Stankov, Andrew Tyner, Shilaan Alzahawi, Saule Anafinova, Eli Awtrey, Erick Axxe, James Bailey, Bert Bakker, Akshaya Balaji, Gabriel Banik, František Bartoš, Henk Berkman, Zachariah Berry, Felix S Bethke, Timothy Brady, Nate Breznau, Sara Capitan, Tabaré Capitán, Laura Caquelin, Kent Jason Cheng, William J. Chopik, Gwen-Jiro Clochard, Tom Coupe, Jamie Cummins, Jianhua Duan, Kevin M. Esterling, Thomas Evans, Nathan Fiala, James Field Verified, Victor Gay, Jing Geng, Johanna Gereke, Ilka Gleibs, Amélie Gourdon-Kanhukamwe, Dmitry Grigoryev, Nicholas Gunby, Paul Hanel, Sanghyun Hong, Sean Houlihan, Nick Huntington-Klein, Kamil Izydorczak, Kristin Jankowsky, Kai J. Jonas, Hansika Kapoor, Sebastian Karcher, Marta Kołczyńska, David Kretschmer, Ljiljana B. Lazarević, Katelin E. Leahy, Jessica Lee, Christopher Limnios, An-Chiao Liu, John Lloyd, Rubén López-Nicolás, Nigel Mantou Lou, Richard Lucas, Maximilian Maier, Daniel Mallinson, Michael McCall, Nikita Mehta, Esteban Mendez, Johannes Michalak, Daniel C. Molden, Faisal Mushtaq, Claudia Neuendorf, Austin Nichols, Gustav Nilsonne, Ernest H O’Boyle, Jeewon Oh, Thomas Ostermann, Abiola Oyebanjo, Radoslaw Panczak, Yuri G. Pavlov, Zoran Pavlovic, Noemi Peter, Kim Peters, Nathaniel D. Porter, Mariah Purol, Arathy Puthillam, Marco Ramljak, Arran T. Reader, W. Robert Reed, Jan Philipp Röer, Ivan Ropovik, Alexander O. Savi, Landon Schnabel, Eric Sevigny, Samuel Shaki, Shishir Shakya, Andrew Soh, Angela Somo, Fatih Sönmez, Eirik Strømland, Jordan Suchow, Anna Szabelska, Anirudh Tagat, Melba Verra Tutor, Karolina Urbańska, Pieter Van Dessel, Elisabeth Julie Vargo, Victor R. Volkman, Ke Wang, Aaron Wichman, Jamal Williams Verified, Fabian Winter, Ferdinand Wintermantel, Nan Zhang Verified, Ignazio Ziano, Cristina Zogmaister, Zorana Zupan, Brian A. Nosek, Timothy M. Errington
| Nature Verified
Abstract Published claims should be reproducible, yielding the same result when the same analysis is applied to the same data1,2. Here we assess reproducibility in a stratified random sample of 600 papers published from 2009 to 2018 in 62 journals spanning the social and behavioural sciences. The authors of 144 (24.0%, 95% confidence interval (CI) = 20.8–27.6%) papers made data available to assess reproducibility and, for 38 others, we obtained source data to reconstruct the dataset.
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We designed an AI tutor that helps college students reason rather than give them answers

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By Saharnaz Babaei-Balderlou, Shishir Shakya, Gaby Clark Verified
| Phys.org Verified
Credit: Pixabay/CC0 Public Domain Students using AI to cheat on homework or tests is a source of much discussion. But some scholars argue the greater risk of students using AI is that they will simply not learn. Approximately 90% of 1,100 U.S. students surveyed at two-year and four-year colleges in 2025 reported using generative AI for everything from drafting assignments to clarifying complex concepts.
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