Reframing the sex debate in scientific research: three frameworks to support rigor without rigidity

Debates about the nature of sex are prominent in scientific, scholarly and public discourses. Scientific as well as societal debates largely focus on whether sex is appropriately conceptualized as a binary, a spectrum, or some other form. These have taken on particular urgency because of highly contested, polarizing, and consequential developments in the global landscape in which the political weaponization of binary sex has escalated. Here we propose three frameworks useful for retaining focus on why sex might be conceptualized in a certain way to address the aims of a given project to help avoid pitting binary versus non-binary approaches against one another in a continued impasse. These three frameworks are (a) sex as a system of classification, (b) sex as a trait, and (c) sex as a dynamic system. We also provide a series of questions and considerations to guide a critical read of scholarship and scientific engagement of sex in ways that might help mitigate the isolating effects of disciplinary silos and advance cross-disciplinary dialogue and collaboration. Thus, rather than recapitulating discussions of how sex should be conceptualized or trying to establish a universally applicable definition of sex, these three frameworks and guiding questions can be drawn on to consider why certain projects might employ particular definitions and methods of operationalization of sex over others, and outline the merits and drawbacks of each. By refocusing our scholarly attention on what sex is empirically being employed to do and why, and providing these frameworks to think with, we hope to bring some essential bridging between those for and those against binary thinking about sex and foster a diversity of approaches that might more effectively build on one another rather than exist in opposition. We can then continue to try to nimbly engage what it is sex is being leveraged to do and why in order to ask how a given conceptualization will help us to learn about a given phenomenon.