I argue that library-based research should be conceived as a particular kind of research system, in contrast to more familiar systems like standard social scientific research (SSSR). Unlike SSSR, library-based research is based on nonelicited sources, which are recursively used and multiply ordered. It employs the associative algorithms of reading and browsing as opposed to the measurement algorithms of SSSR. Unlike SSSR, it is nonstandardized, nonsequential, and artisanally organized, deriving crucial power from multitasking. Taken together, these facts imply that, as a larger structure, library-based research has a neural net architecture as opposed to the von Neumann architecture of SSSR. This architecture is probably optimal, given library-based research's chief aim, which is less finding truth than filling a space of possible interpretations. From these various considerations it follows that faster is not necessarily better in library-based research, with obvious implications for library technologization. Other implications of this computational theory of library research are also explored.
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