On Preprints (and Journals)

The good folks at the Academic Life Histories blog asked if I wouldn’t mind contributing some thoughts about preprints.

I’ve been writing scientific papers since 2010, not counting the physics paper I landed on as an undergraduate in 1999. For the last three years, I’ve put almost every paper I’ve written on a preprint server before submitting it to a journal. In certain corners of academia, this fact warrants an explanation. Some want to argue it’s a bad idea, others may be curious, and others may be fully on board but just want to hear another perspective. This is my perspective. Caveat: Some of my characterizations about the process of doing science, or of the peer review experience, may not ring true for some readers. So it goes.

I think preprints are great. A big part of why preprints are great is because they aren’t journal articles. As such, I’m going to start out by talking about the problems with journals and with peer review, and then swing back around to talk about how preprints help us solve some of these problems. I also think journals are still valuable and I don’t want them to go away, and so I view preprints as a valuable complement rather than as a replacement. Here we go. 

Read the rest here.

Interactional Complexity and Human Societies

We are interested in understanding various aspects of human societies.Since the structural and functional behavior of human societies undoubtedly qualifies as a complex system, it is useful to discuss certain terminology and philosophical concepts related to the organization of complex systems. William Wimsatt’s (1974) notion of interactional complexity will be particularly useful but is not widely appreciated, and so I will go into some detail to clarify this concept.

Decompositions and descriptive complexity

Stuart Kauffman (1971) presciently noted that, when describing a complex system, different descriptions of the system and resulting articulations of parts, or decompositions, might be varyingly useful depending on the purpose of the analysis, and that these descriptions might be non-isomorphic. That is, the delineations of the constituent parts may not coincide between different decompositions.

Wimsatt’s major insight was to note that relationships between the different decompositions of a system could be used to denote their intrinsic complexity. As an example, he compared a chunk of granite with the fruit fly Drosophila melanogaster (see Fig. 1 in Wimsatt, 1974). The chunk of granite can be described via a decomposition into parts grouped by (for example) chemical composition, thermal conductivity, electrical conductivity, density, or tensile strength. Although these decompositions are not completely isomorphic, some of the boundaries between parts are shared between each description (e.g., a section with a specific density will also have a specific tensile strength and chemical composition relative to the neighboring parts). The fruit fly, meanwhile, can also be described by decomposition into parts based on (for example) anatomical organs, cell types, developmental gradients, biochemical reactions (i.e., the local presence of reaction types), or physiological systems (as described by cybernetic flow diagrams). In contrast to the granite chunk, the boundaries between the parts of the various decompositions are not spatially coincident, and indeed, the last two items on the list are not evenly clearly describable in a coherent spatial manner. Wimsatt introduced the term descriptive complexity to indicate the degree to which the spatial boundaries of various descriptive decompositions coincide. A fruit fly is thus more descriptively complex than a chunk of granite.

Interactional complexity

A system can often be described in terms of subsystems, each of which has a specific set of parts. We can constrain this description by specifying that, for the parts within these subsystems, the causal relations with other parts within the subsystem should be much stronger than the causal relations with parts from other subsystems. Indeed, this constraint helps delineate each subsystem from the others, and might be seen as the degree to which a valid prediction of the system behavior could assessed by only considering the behavior of each subsystem, ignoring interactions between them. Remember, however, that there may be many useful decompositions of the system into subsystems, each with its own set of constituent parts.

We say that a system under these constraints is interactionally simple if there are only weak causal relationships between the parts of a subsystem in one decomposition and the parts of a different subsystem in a different decompositional description, and interactionally complex to the degree to which those causal relations are strong. Put more bluntly, a system has a high degree of interactional complexity if an investigator must consider the system from more than one theoretical perspective (i.e., more than one decomposition) in order to make useful predictions. Driving the point home, Wimsatt writes, “If the system is descriptively complex and is also interactionally complex for more than a very small number of interactions, the investigator is forced to analyze the relations of parts for virtually all parts in the different decompositions, and probably even to construct connections between the different perspectives at the theoretical level.” (1974, p. 74). Forty years after Wimsatt’s paper first appeared, this idea may no longer be revelatory, but I maintain that it is still underappreciated.

Human societies are interactionally complex

It seems obvious that human societies are descriptively complex. We can describe societies at the level of individuals, in terms of nuclear families, kin groups, subcultures, and social classes. We can also include infrastructure and transportation, livestock and farming, religious rituals and linguistic traditions. This is all on top of the descriptive complexity of an individual human, which I believe we can agree is at least as great as that of a fruit fly.

Importantly, human societies, and the human groups that comprise societies, are also interactionally complex. Perspectives include genetic, neurological, cognitive, familial, cultural, and ecological. To at least some extent, we can’t ignore any of them.


  • Kauffman, S. A. (1970). Articulation of parts explanation in biology and the rational search for them. In: PSA 1970, ed. R. C. Buck & R. S. Cohen, pp. 257–72. Philosophy of Science Association.
  • Wimsatt, W. C. (1974). Complexity and organization. In: PSA 1972, ed. K. Schaffner & R. S. Cohen, pp. 67–86. Philosophy of Science Association.