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of intervening in the natural world to isolate variables for testing came to dominate virtually all of the natural sciences for hundreds of years. Scientists in chemistry, biology, and even the social sciences attempted to copy (with varying degrees of success) the physics-inspired model of identifying single constituents of interesting systems, seeing how those constituents behaved when isolated from each other (and, a fortiori, from a complicated external environment), and using that information to deduce how collections of those constituents would behave in more realistic circumstances. This approach was enormously, earth-shatteringly, adverb-confoundingly successful, and gave us virtually all the scientific advances of the 18th, 19th, and 20th centuries, culminating in the triumph of physics that is quantum mechanics, as well as the more domain-specific (if no less impressive) advances of molecular biology (studying the gene to understand the organism), statistical mechanics (studying the particle to understand the thermodynamic system), and cognitive neuroscience (studying the neuron to understand the brain), just to name a few.

Moreover, this way of thinking about things came to dominate the philosophy of science (and scientifically-informed metaphysics) too. Many of the influential accounts of science developed in the 19th and 20th centuries rely (more or less implicitly) on this kind of model of scientific work. The logical positivists, for whom science was a matter of deduction from particular observations and a system of formal axioms perhaps exemplify this approach, though (as Hooker [2011a] argues), the Popperian model of theory generation, experimental data collection, and theory falsification also relies on this decomposition approach to scientific work, as it assumes that theorists will proceed by isolating variables to such a degree that cases of direct falsification will (at least sometimes) be clearly discernible. The account of science developed in Chapter