Who knew I could stay up late reading about the biology, politics, and sociology of a hormone. Really enjoyed this overview of scientific methodology and how it collides with public opinion. I highlighted so many telling passages, but here are a few of my favorites for those who don't have time to read the whole book:
▪ When we say we don’t take the science literally, we mean that we’re aware that scientific findings aren’t served up on a platter by Mother Nature. Instead, they are constructed out of specific research questions, the tools scientists use, and an enormous array of methodological choices, including what to measure and how, which groups or situations to compare, what statistical methods to use, and on and on. Critical excavation of science is not the same as rejecting facts, or saying that all observations or all evidence is relative. As the sociologist of science Bruno Latour observed more than a decade ago, “The question [for critical science and technology studies scholars] was never to get away from facts but closer to them, not fighting empiricism but, on the contrary, renewing empiricism.”
▪ ... agnotology, or the study of ignorance and how it is created, sustained, and used, is as important as epistemology, the study of knowledge. Asking “What don’t we know, and why don’t we know it? What keeps ignorance alive, or allows it to be used as a political instrument?,” scholars have examined ignorance in domains that include global climate change, military secrecy, female orgasm, environmental justice, archaeology and land claims, racial ignorance, and more.
▪ There are seasonal variations, too, but there is no universal pattern of circadian and seasonal variations with T. And some variation is just idiosyncratic. Dr. William Crowley of the Reproductive Endocrine Unit at Massachusetts General Hospital has observed “a funny disconnect between one measurement and a later one” in a number of men he has studied: they have very low T levels at one point but later have a “perfectly normal testosterone profile.” What’s more, the daily fluctuations in T that have been found in US and European populations aren’t found everywhere across the globe. And while many different studies around the world have found seasonal variations, the peaks and troughs don’t come at consistent times, and it isn’t clear what’s driving them. Sunlight? Temperature? Work patterns? Variations have been observed in people whose activities have seasonal patterns, like athletes during the off-season, the training season, and the competitive season. Others, such as farmers in rural Bolivia, who have huge variations in activity across the seasons, didn’t show any seasonal variation in T over the course of a year. These variations across populations, within populations, and within individuals are significant but not well understood. For most research questions, it doesn’t make sense to just take one T measure and think that you have captured an individual’s T as if it were a stable trait. But when taking multiple measures, it’s important to try to minimize sources of variation in T that aren’t relevant to the research question. Thus, most researchers measure T at the same time of day for all subjects, and for women they also factor in hormonal contraception and the menstrual cycle.
▪ If 15 percent of men with excellent health have T below the normal range, what’s the criterion for calling that range “normal”? This matters in medicine, but also in sports: how the “normal” ranges of T are calculated for men and women is central to a debate about regulating women athletes...
▪ Multiplicity is not, in the end, the main narrative that we pick up, but it is a crucial background fact. To be clear, the specificities and multiplicity of T do not mean there is no hope for a scientist who wants to pin T down. Scientists aren’t oblivious to this by any means—researchers working with T are the ones who have elaborated the importance of the different versions, after all. But the specificities have a way of slipping out of view at crucial moments in studies, and especially in review articles and other synthetic statements about what “T” (singular) does. The stubborn insistence on the specific version of T that does things in the body, that relates to other aspects of bodies and reciprocally engages with behaviors, means that synthetic statements are more elusive. That may frustrate researchers who are taught that good science is characterized by simplicity. But the apparent simplicity of this molecule is an illusion.
▪ It is helpful also to take an agnotology perspective—that is, to think not only about what has been persistently unknown or forgotten about female reproduction, but also about why these elements are forgotten, and how precisely that forgetting happens
▪ As with the studies of aggression and T that suggest patterns of violence and criminality can be explained by too much T, the power posing narrative uses T talk to shrink a huge social problem to the microenvironment of an individual body. If power posing can, as Cuddy says, “significantly change the way your life unfolds,” why bother directly confronting structural inequality? Standing with your hands on your hips provides a fast, individualized solution that is much more manageable than challenging entrenched systems. It’s the kind of argument that appeals to a liberal feminist sensibility, even as it obscures the radically different relationships to power among the homogenized category of “women.” In spite of the feminist sheen, the power posing approach actually counters a mainstay of feminist analysis and activism: gender inequality stems from social formations, not from biology. For those researching power posing, power is internal: postures shift state of mind and hormones, which in turn shift behaviors, creating power itself.
▪ In keeping with this cultural habit of imagining risk as risking money, most researchers studying risk-taking treat financial behavior as the epitome of risk-taking in humans. Of course, this skips over obvious problems, such as that you have to have money to risk money, and that who has money is determined by all kinds of external factors, like gender systems, social class, and global economic relations, as well as idiosyncratic life events.
▪ After three strikes with their planned comparisons, they turned to other measures that might show a link between cortisol and losses. This part of the paper reads a bit like a detective story, as the researchers detail their meticulous search for correlations, signaling the exploratory nature of their process with phrases like “we therefore looked” and “we suspected that” and “consequently, we looked to see whether …” You can almost hear the ship creaking as they turn their analysis to meet their data. This is the very definition of p-hacking.
▪ Jens Zinn, a sociologist who studies the phenomenology of risk, argues that “it does not make sense to speak about risk-taking when the decision-maker is not affected by the outcomes (which instead affect others). This could be called risk-making (for others) rather than risk-taking and follows a different logic.” The traders weren’t monetarily unaffected, but the bulk of the money at stake was not theirs. In other areas of life, people whose risk-taking ripples outward to create negative consequences for others, or whose risks break social and legal rules, are sometimes labeled as “antisocial,” “externalizers,” or even sociopaths. These terms are used in some of the studies on T and risk-taking, but tellingly, the studies of risk-taking among traders, CEOs, entrepreneurs, and business students don’t frame negative or irresponsible behaviors this way, even decidedly illegal activities like insider trading, options backdating and tax evasion, or cheating in business negotiations.
▪ The dangerous things that some groups of people do as a matter of course because of role expectations and material constraints are not typically examined as risks. For example, the epidemiologists Karen Messing and Jeanne Mager Stellman have documented the surprisingly extensive toxic exposures and high accident rates involved in domestic labor, a pattern obscured by the widespread notion of home as a “safe place.”32
So it’s not just desperation that makes people do dangerous things, it’s expectations, norms, and the daily circumstances of inequality. Consider the mundane behavior of asking for directions. This isn’t inherently risky, but the context can make it so, depending upon who you are, where you are, and whom you ask. In recent years, there have been innumerable accounts of black people going about their normal daily routines—asking directions, waiting in a cafe for business associates, playing in a park, driving, resting in a student lounge, and barbecuing are a few examples—who have faced extreme consequences ranging from arrest to assault to murder, at the hands of both civilians and the police, so many of whom have been white. Likewise, as Fine has pointed out, childbirth for a woman in the United States is about twenty times more likely to be fatal than skydiving. Even this surprising level of risk masks huge disparities by race and class. Black women continue to experience devastatingly high maternal mortality rates: more than four black women die for every thousand live births, while just over one white woman does. Native American and Alaskan Native women die at twice the rate of white women.33
▪ Science is not only storytelling, and this is why we insist on following the constructs and thinking about which specific version of risk or T is being mobilized in particular studies. But one story—the idea that T, via sexual selection, has ensured the pairing of maleness with a whole suite of traits and behaviors—is the glue that holds a whole body of research together. Narratives and data can also be fit into the rubric of “floaters” and “sinkers”: floaters are the stories and bits of data that get picked up from researchers’ discussions, abstracts, and titles and get cited in subsequent research, and the sinkers are the bits that don’t fit, the awkward gaps between hypothesis and data, the multiple analyses that are done offstage and never again mentioned. The data on risk-taking and T are weak at best, and certainly chaotic. But the narrative has a pleasing parsimony: T increases risk-taking.
▪ As we’ve seen, researchers make radically different uses of theories and data on T to explore patterns of parenthood in humans. At one extreme, purported racial variations in T and reproductive strategies are taken up to legitimize white supremacy and argue that human races literally have traveled different evolutionary trajectories. At the other extreme, shifts in T associated with the nurturing components of parenting are used to break the age-old designation of T as “masculine.” But it is important to be alert to the background narratives about good and bad parenting that are potentially activated by this work, especially when it is framed in terms of investments in offspring—even when these normative judgments run counter to researchers’ explicit commitment to a non-normative approach to human behavioral variations.
▪ It’s worth repeating that most of the researchers who use data on T to understand evolution and human parenting in no way endorse the uptake of that material for racist arguments. But resonance doesn’t require their active engagement. Synthetic theories about the evolution of human behavior, and about T as a mechanism in those processes, are like the warp and weft of a scientific and cultural fabric. Researchers don’t weave the fabric alone—no one could, as the field of data required is too vast. Instead, they must rely on other researchers’ work to supply some of the threads that get woven into the overall piece. Those threads, as well as the structure and language of the theory, build racial content into challenge hypothesis work in humans.
▪ Writing about this work presented us with similar challenges. Whether a citation is laudatory or outright condemnation, it underscores the importance of a piece of writing by showing that others have taken it seriously enough to engage with it. Links across studies lend each other mutual support, reinforcing the “fact value” of each through citation. We have opted to write about a number of egregiously racist studies in this chapter, especially, and wish that we could do so without citing them. As scholars, we need better strategies for responsibly identifying deeply problematic work without adding to its fact value.