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Trust, Transparency, and Replication in Political Science

Published online by Cambridge University Press:  03 January 2017

David D. Laitin  and
Rob Reich
David D. Laitin
Affiliation:
Stanford University
Rob Reich
Affiliation:
Stanford University
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Abstract

Striving better to uncover causal effects, political science is amid a revolution in micro-empirical research designs and experimental methods. This methodological development—although quite promising in delivering new findings and discovering the mechanisms that underlie previously known associations—raises new and unnerving ethical issues that have yet to be confronted by our profession. We believe that addressing these issues proactively by generating strong, internal norms of disciplinary regulation is preferable to reactive measures, which often come in the wake of public exposés and can lead to externally imposed regulations or centrally imposed internal policing.

Type
Articles
Information
PS: Political Science & Politics , Volume 50 , Issue 1 , January 2017 , pp. 172 - 175
Copyright
Copyright © American Political Science Association 2017 

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References

REFERENCES

Ayres, Ian and Unkovic, Cait. 2012. “Information Escrows.” Michigan Law Review 111 (145): 145.Google Scholar
Green, Donald and Gerber, Alan S.. 2002. “Reclaiming the Experimental Tradition in Political Science.” In Political Science: State of the Discipline, ed. Katznelson, Ira and Milner, Helen V., 805–32. New York: W.W. Norton.Google Scholar
Hainmueller, Jens, Mummolo, Jonathan, and Xu, Yiqing. 2016. “How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice.” Social Science Research Network. Available at http://ssrn.com/abstract=2739221.Google Scholar
Ioannidis, John. 2005. “Why Most Published Research Findings Are False.” PLoS Medicine 2 (8): 124.Google Scholar
King, Gary. 1995. “Replication, Replication.” PS: Political Science and Politics 28: 443–99.Google Scholar
Laitin, David D. 2013. “Fisheries Management.” Political Analysis 21 (1): 42–7.Google Scholar
Malesky, Edmund, Schuler, Paul, and Tran, Anh. 2012. “The Adverse Effects of Sunshine: A Field Experiment on Legislative Transparency in an Authoritarian Assembly.” American Political Science Review 106: 762–86.Google Scholar
McCubbins, Mathew D. and Schwartz, Thomas. 1984. “Congressional Oversight Overlooked: Police Patrols versus Fire Alarms.” American Journal of Political Science 28 (1): 165–79.CrossRefGoogle Scholar
Miguel, Edward. 2014. “Promoting Transparency in Social Science Research.” Science 343 (6166): 30–31.Google Scholar
Moore, Barrington. 1966. Social Origins of Dictatorship and Democracy: Lord and Peasant in the Making of the Modern World. Boston: Beacon Press.Google Scholar
Neuroskeptic. 2012. “The Nine Circles of Scientific Hell.” Perspectives on Psychological Science 7 (6): 643–4.CrossRefGoogle Scholar
Simonsohn, Uri, Nelson, Leif D., and Simmons, Joseph P.. 2014. “p-Curve: A Key to the File Drawer.” Journal of Experimental Psychology: General 143 (2): 534–47.Google Scholar
Singal, Jesse. 2015. “The Case of the Amazing Gay-Marriage Data: How a Graduate Student Reluctantly Uncovered a Huge Scientific Fraud.” Science of Us. Available at http://nymag.com/scienceofus/2015/05/how-a-grad-student-uncovered-a-huge-fraud.html Google Scholar