Compare methods

	Field Experiment in Politics	Field Experiment
Field	Political Science	Experimental design
Family	Process / pipeline	Process / pipeline
Year of origin	2000	1920s–1930s (agriculture); 1990s–2000s (social sciences)
Originator	Gerber & Green (modern political field experiments)	Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004)
Type	Randomized experiment conducted in a real political setting	Experimental design
Seminal source	Gerber, A. S., & Green, D. P. (2000). The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment. American Political Science Review, 94(3), 653–663.	Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055.
Aliases	Political field experiment, Get-out-the-vote experiment, GOTV experiment, Voter mobilization experiment	field trial, natural field experiment, randomized field experiment, field RCT
Related	4	5
Summary	A field experiment in political science randomizes a real intervention — such as a get-out-the-vote canvass, mailing, or phone call — among genuine political actors in their natural environment and compares behavioral outcomes like validated turnout. Revived for the discipline by Gerber and Green's 2000 voter-mobilization study and codified in their 2012 textbook, the approach combines the causal leverage of randomization with the realism of consequential, real-world settings, while carefully distinguishing the effect of being assigned a treatment from the effect of actually receiving it.	A field experiment applies the logic of a randomized controlled trial in a naturally occurring, real-world environment rather than an artificial laboratory. Participants are randomly assigned to treatment and control conditions while going about everyday activities, allowing researchers to estimate causal effects with high internal validity while preserving a level of ecological realism that laboratory settings cannot offer. The design is especially prominent in economics, public health, political science, and development research.