Martie G.Haselton, Ph.D. | University of California, Los Angeles

Research Overview

I am an interdisciplinary evolutionary scientist interested in how evolution has shaped the social mind. I am broadly interested in human intimate relationships and sexuality, their endocrine foundations, and their links to outcomes with broad social relevance, including health and well-being. To explore these topics, I do laboratory experiments, hormone assessments, genetic typing, surveys, and field studies – in short, whatever method best fits the research question.

Research Topics

  • Bias in Social Judgment
  • Cues of Ovulation
  • Darwinian Health and Medicine
  • Effects of Ovulation on Women's Desires and Social Behavior
  • Mate Choice
  • MHC Genes and Relationships
  • Pregnancy and Postpartum Adaptations
  • Relationship Formation and Immune Function
  • Social Endocrinology of Parenting
  • Social Regulation of Fertility
  • Sex Differences
  • Women's Sexuality

Current Projects

Fertility, Hormones, and Social Relationships

One of my primary areas of research concerns the role of reproductive hormones in romantic and sexual relationships – relationships that are undoubtedly among the most important in human life. 

In women, fertility is fleeting, spanning just a few days each month. Because these are the only days during which sex could have led to conception, we have hypothesized that the mechanisms guiding women’s sexual decision making have evolved to take fertility into account. Recent research in my lab has been intensely focused on testing this general idea. (For examples of this work, see Haselton & Gangestad, 2006; Larson, Haselton, et al., 2013Lieberman, Pillsworth, & Haselton, 2011.)

In related work, we have collected photographs, vocal recordings, and body odor samples from women in order to examine whether there are cues of ovulation that others could detect and respond to. For example, a straightforward evolutionary prediction is that men should evolve to detect any available cues of ovulation in women and find these high­‐fertility cues sexually attractive. We have found that, relative to low‐fertility days of the cycle, on high­‐ fertility days of the cycle, women wear more attractive and revealing clothing (Durante, Li, and Haselton, 2008; Haselton et al., 2007), their vocal pitch goes up (Bryant & Haselton, 2009), and their body odors are rated as more attractive by men (Gildersleeve et al., 2012). We summarize this work in a review paper entitled, Can Men Detect Ovulation? (Haselton & Gildersleeve, 2011). As we argue in the paper, this work is noteworthy because it challenges the long‐held assumption that human ovulation is concealed. These findings have far reaching implications for understanding fluctuations in couples’ attraction, conflict, and relationship dynamics.

The literature in this area has grown at a rapid pace. I review the literature and underlying theory in two recent papers (Haselton & Gildersleeve, 2016; Gangestad & Haselton, 2015), and synthesize it in meta-analyses. The first of these meta-analyses, concerning shifts in mate preferences, indicated that effects are robust, though small, and not attributable to publication bias or flexible research practices (Gildersleeve, Haselton, & Fales, 2014a; Gildersleeve, Haselton, & Fales, 2014b). It is possible that effect sizes are small because methods used by many researches are imprecise (e.g., using women's recalled last menstrual onset and counting forward to estimated windows of fertility). Steve Gangestad and I, with several colleagues, discuss these methodological issues, present simulations that document how imprecise measures can depress effect sizes, and make recommendations to improve methods in the literature (Gangestad et al., 2015). Ovulation cycle effects have generated broad interest and some controversy. I discuss these issues and their historical foundations in my forthcoming book, Hormonal. I also argue that concerns about the political implications of hormone effects are misplaced and more discussion of the research, not less, will improve women's health and well being.

I have also investigated the role of social factors and hormones on women's reproductive health. With a recent postdoctoral student working in my lab, for example, I have examined the effects of postpartum hormones on maternal mental health (Hahn­‐Holbrook, Dunkel Schetter, & Haselton, 2013; Hahn‐Holbrook, Hahn, & Haselton, 2011).

Error Management and Adaptive Biases

The social world is filled with uncertainty. People conceal their true intentions and actively deceive others about those intentions. People may also remain undecided about what their future decisions will be in an unfolding social relationship, which further complicates the task of judging their intentions and future behavior. Because of this uncertainty, forming social judgments about others is one of the fundamental challenges of social living: Is a person truthful or deceptive? Peaceful or aggressive? Sexually interested or just being nice? My research on what I have termed error management theory (EMT; Haselton & Nettle, 2006) concerns these social judgments and aims to explain cases in which they are systematically biased.

Building on signal detection theory, EMT proposes that when the costs of false positive and false negative errors were asymmetrical over evolutionary history, selection will have designed psychological adaptations biased in the direction of the less costly error. For example, because the reproductive costs of missing a sexual opportunity were high for ancestral men, natural selection may have favored a bias in men that leads them to overestimate a woman’s sexual interest under uncertain conditions (Haselton & Buss, 2000; for a related appraoch in evolutionary medicine, see Nesse, 2001, on The Smoke Detector Principle). 

EMT has led to new predictions and empirical findings across a variety of areas (for reviews see Haselton & Galperin, in press; Haselton et al., 2009; Haselton & Funder, 2006). A key conceptual implication of the theory is that selection has led to adaptations that are biased by design and functioned to help ancestral humans avoid particularly costly errors. This contrasts with the common idea that unbiased and maximally accurate systems are rational. With several colleagues, I have argued that the error management is a basic principle of life that can help to explain biased behavior of collective entities (e.g., nation states), individuals (humans and other animals), and even genes (Johnson, Blumstein, Fowler, & Haselton, 2013)