Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general‐purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long‐term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder‐brains to reader‐brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core.

In their 2010 book, Biology's First Law, D. McShea and R. Brandon present a principle that they call ''ZFEL,'' the zero force evolutionary law. ZFEL says (roughly) that when there are no evolutionary forces acting on a population, the population's complexity (i.e., how diverse its member organisms are) will increase.Here we develop criticisms of ZFEL and describe a different law of evolution; it says that diversity and complexity do not change when there are no evolutionary causes.

The contextual approach is a prominent framework for thinking about group selection. Here, I highlight ambiguity about what the contextual approach is. Then, I discuss problematic entailments the contextual approach has for what processes count as group selectionentailments more troublesome than typically noted. However, Sober and Wilson's version of the Price approach, which is the main alternative to the contextual approach, is problematic too: it leads to an underappreciated paradox called the vanishing selection problem and thereby generates the wrong qualitative account of whether group selection is occurring in a certain family of cases. In response, I develop an account of group selection that can deal with the counterexamples to both the contextual approach and the Price approach. I then discuss the role that contextual analysis can continue to play in the discussion of individual fitness and metapopulation evolution.

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Fictionalists believe that scientific models are about model systems that are imaginary. Weisberg has claimed that fictionalism is indefensible because many scientific models are about model systems that are unimaginable. According to a certain account of imagination, what Weisberg says is plausible. According to another, more defensible account of imagination, it is not. I discuss these issues within the context of an allegedly unimaginable model system in ecology, but the conclusions I draw are more general. I then describe how fictionalism should be recast in order to deal with Weisberg's critique.