It's a convenient shorthand to treat sex/gender as dichotomous, and Benenson et al. necessarily rely on studies that use this shorthand exclusively. However, it's important to emphasize that sex/gender is, in fact, a multifaceted bimodal continuous variable. The authors have done outstanding work synthesizing copious cross-cultural data, unequivocally demonstrating stronger self-protective reactions in females. However, whether these differences are truly a “series of evolved female adaptations” that constitute an adaptive survival strategy, or a collection of adaptations and evolutionary by-products remains in question.

Are all sex differences adaptations? Sex differences in a psychological trait can serve as supporting evidence for an evolved psychological mechanism. However, sex differences are neither necessary nor sufficient to identify a psychological adaptation or differentiate a purported adaptation from an evolutionary by-product (an evolved trait inexorably linked with an adaptation). It's likely that some of Benenson et al.'s proposed female self-protection adaptations have continuous factors other than sex underlying the “sex differences” and that some of these differences are (either functionless or fitness-enhancing) evolutionary by-products of these underlying factors.

For example, Benenson et al. note that women “overestimate the speed of incoming stimuli” more than men (sect. 7.1). Auditory perception research shows that both sexes perceive incoming sound sources as faster and closer than equivalent receding sounds and as arriving sooner than they actually do (Neuhoff, Reference Neuhoff2001, Reference Neuhoff2016; Neuhoff, Planisek, & Seifritz, Reference Neuhoff, Planisek and Seifritz2009). This “auditory looming bias” is an adaptation that provides a margin of safety and affords more time than expected to prepare for a threat's arrival (Neuhoff, Reference Neuhoff1998). Women exhibit a larger bias than men and are therefore afforded greater self-protection (Neuhoff, Hamilton, Gittleson, & Mejia, Reference Neuhoff, Hamilton, Gittleson and Mejia2014; Neuhoff et al., Reference Neuhoff, Planisek and Seifritz2009; Schiff & Oldak, Reference Schiff and Oldak1990). If we stop there, we have a story that fits nicely with “self-protection as an adaptive female strategy.”

However, subsequent work showed that physical strength is correlated with the looming bias. The more formidable one is, the smaller the bias (Neuhoff, Long, & Worthington, Reference Neuhoff, Long and Worthington2012). Importantly, this relationship persists even when within-sex correlations are calculated. Thus, strength is more important than biological sex in explaining reactions to looming sounds. The sex difference is simply a by-product of a mean sex difference in strength, indicating vulnerability to threat. Sample sizes in these looming studies are not as large as those in the work reviewed by Benenson et al., and this sex difference was not included in their analysis. Nonetheless, other sex differences in self-protection may also be by-products of a more explanatory continuous variable.

For example, Benenson et al. identify sex differences in pain as a female self-protective adaptation. However, men and women also differ in sex hormone levels. Although the effects of estrogen and testosterone on pain perception are complex, there is ample evidence showing that under many conditions, testosterone decreases responses to pain, while estrogen increases it (Craft, Reference Craft2007; Flake, Hermanstyne, & Gold, Reference Flake, Hermanstyne and Gold2006; Ji, Hu, Li, & Traub, Reference Ji, Hu, Li and Traub2018; Ji, Tang, & Traub, Reference Ji, Tang and Traub2008; Lesnak, Inoue, Lima, Rasmussen, & Sluka, Reference Lesnak, Inoue, Lima, Rasmussen and Sluka2020; Schertzinger, Wesson-Sides, Parkitny, & Younger, Reference Schertzinger, Wesson-Sides, Parkitny and Younger2018). In animal models, ablation of estrogen receptors eliminates sex differences in pain entirely (Li et al., Reference Li, Fan, Warner, Xu, Gustafsson and Wiesenfeld-Hallin2009). In humans, testosterone therapy successfully relieves fibromyalgia pain (Dubick, Ravin, Michel, & Morrisette, Reference Dubick, Ravin, Michel and Morrisette2015; White et al., Reference White, Brown, Gyurik, Manganiello, Robinson, Hallock and Yeo2015).

Thus, reproductive hormones (whose main evolutionary job is facilitating reproduction) can plausibly explain sex differences in pain perception. This hypothesis is buttressed by data showing little evidence of sex differences in pain among children (Boerner, Birnie, Caes, Schinkel, & Chambers, Reference Boerner, Birnie, Caes, Schinkel and Chambers2014). Importantly, these pain–hormone relationships are robust within-sex (Ivkovic, Racic, Lecic, Bozovic, & Kulic, Reference Ivkovic, Racic, Lecic, Bozovic and Kulic2018; Kato et al., Reference Kato, Shigehara, Kawaguchi, Izumi, Kadono and Mizokami2020). The dichotomous shorthand that we use for “sex” obscures the bimodal yet continuous underlying potential cause of the “sex difference.”

Rather than an adaptation, sex differences in pain may be an exaptation of the effects of reproductive hormones. Variability in sex hormones may indeed currently enhance female fitness in response to pain. However, the main adaptive problem sex hormones solved was facilitating sexual reproduction. This reasoning applies to many of Benenson et al.'s other proposed female self-protection adaptations that are influenced by hormones, including immune function, fear, stress, autoimmune disorders, responses to vaccines, depression, anxiety, and emotion recognition (Amiaz & Seidman, Reference Amiaz and Seidman2008; Dirlikov, Lavoie, & Shem, Reference Dirlikov, Lavoie and Shem2019; Glover et al., Reference Glover, Mercer, Norrholm, Davis, Duncan, Bradley and Jovanovic2013; Hermans, Putman, Baas, Koppeschaar, & van Honk, Reference Hermans, Putman, Baas, Koppeschaar and van Honk2006; Maeng & Milad, Reference Maeng and Milad2015; Rehbein et al., Reference Rehbein, Kogler, Hornung, Morawetz, Bayer, Krylova and Derntl2021; Rosen, Ham, & Mogil, Reference Rosen, Ham and Mogil2017; Ruggieri, Anticoli, D'Ambrosio, Giordani, & Viora, Reference Ruggieri, Anticoli, D'Ambrosio, Giordani and Viora2016). Underlying continuous factors might also explain responses to some social threats. For example, sex differences in smiling may be explained by variability in dominance and affiliation, as even within-sex variability in smiling predicts physical dominance (Hess, Adams, & Kleck, Reference Hess, Adams and Kleck2005; Ketelaar et al., Reference Ketelaar, Koenig, Gambacorta, Dolgov, Hor, Zarzosa and Wells2012; Kraus & Chen, Reference Kraus and Chen2013).

Abraham Maslow famously said, “If all you have is a hammer, everything looks like a nail.” This quote perfectly encapsulates the current state of research on sex differences. Benenson et al. acknowledge the dubious wisdom of treating sex/gender as binary, but it was the only type of data available for their synthesis. Historically, researchers (myself included) have failed to treat sex/gender as continuous. Thus, the only analysis tool currently available is a “binary hammer” that destroys the nuance of the continuum and masks other potentially more explanatory constructs.

As scientists, we need to do better to examine sex/gender as a multifaceted continuous variable because it's good science and it has critical implications for equality and public policy. Dichotomizing continuous variables obscures individual differences and nonlinear relationships, underestimates effect size, reduces statistical power, and decreases reliability (MacCallum, Zhang, Preacher, & Rucker, Reference MacCallum, Zhang, Preacher and Rucker2002). This mismeasurement leads to poor policy recommendations and greater inequality. For example, in a startling commentary on Campbell's (Reference Campbell1999) original “staying alive” target article, which posited greater female self-protective behaviors in risk-taking and aggression, Browne (Reference Browne1999) concluded that perhaps women were not fit to serve in military combat or as business executives. Clearly, looking at continuous data through a dichotomous lens misses a richer explanation of the phenomena (Cameron & Stinson, Reference Cameron and Stinson2019).