reported using only the original pilot data which had not been randomized; see Jamison (1980). Although there was quite a gap in time between these early efforts and the new post-millennial age of ‘randomistas’ in development economics, there is a clear link between them in the work of such scholars as Michael Kremer.

# <u>7. Conclusion</u>

This paper has argued that a single notion of randomized assignment captures not only the usual application of random allocation into treatment and control groups, but also more broadly any randomization that controls for observable and unobservable factors. This allows for the legitimate direct comparison of empirical observations across conditions in a broad range of environments, and hence for ascriptions of causality. Such an approach appears to be novel in the literature on this topic, and it allows a more holistic vision of the development of the concept over time. In particular we expand beyond a focus on clinical medicine, or indeed any single discipline (e.g. limited previous work on experimental economics, psychology, and social policy), and look at some of the interconnections between them. Several specific examples that have not been highlighted in the existing literature are also resurrected en route.

In what can be called the first phase of the introduction of randomization to empirical social science, a scattering of 19<sup>th</sup> -century research studies consciously employed the technique to good effect. Notable examples include the 1835 Nuremberg salt trial and the 1884 Peirce psychophysics experiment. Although these were completely rigorous even by modern standards, they did not immediately spawn imitators or enjoy influence. One possible reason is that they were simply unknown and unlucky, but there are two more plausible explanations. A purely practical possibility is that these experiments did not formally involve the _allocation_ of subjects into groups, but rather randomization across treatments. It may not originally have occurred to practitioners that randomization could just as easily be used for allocation, which was the most typical need. But the most likely explanation is that the main goal was to provide a valid comparison, and no particular distinction was made at the time between randomization and other methods for doing so, such as matching and alternation. We see support for this in the work of Fibiger (1898), who equates alternation with randomization, and in the multiple educational psychology studies of the early 20<sup>th</sup> century.

What had been a purely practical concern for learning (and debating one’s colleagues, as in homeopathy versus allopathy) became a more conceptual or theoretical concern in the 20<sup>th</sup> century. Issues surrounding causality and epistemology raised the bar for social and clinical science. It became increasingly necessary to be able to claim that certain discrete factors led to certain outcomes with a high degree of confidence in that knowledge, in order to convince one’s peers as well as policy makers. Although these issues were explicitly articulated in the late 1940s and 1950s, the more explanatory transition period that gave rise to them displays a remarkable convergence across fields. In particular, one of the main contributions of the paper is the argument that four related but distinct disciplines experienced the introduction of randomized assignment within just a few years of one another around 18