Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study ( n = 127), science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants’ preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science.

ABSTRACT:We examined the influence of menu calorie labels on fast food choices in the wake of New York City's labeling mandate. Receipts and survey responses were collected from 1,156 adults at fast-food restaurants in low-income, minority New York communities. These were compared to a sample in Newark, New Jersey, a city that had not introduced menu labeling. We found that 27.7 percent who saw calorie labeling in New York said the information influenced their choices. However, we did not detect a change in calories purchased after the introduction of calorie labeling. We encourage more research on menu labeling and greater attention to evaluating and implementing other obesity-related policies.

Are humans intuitively altruistic, or does altruism require self-control? A theory of social heuristics, whereby intuitive responses favor typically successful behaviors, suggests that the answer may depend on who you are. In particular, evidence suggests that women are expected to behave altruistically, and are punished for failing to be altruistic, to a much greater extent than men. Thus, women (but not men) may internalize altruism as their intuitive response. Indeed, a meta-analysis of 13 new experiments and 9 experiments from other groups found that promoting intuition relative to deliberation increased giving in a Dictator Game among women, but not among men (Study 1, N = 4,366). Furthermore, this effect was shown to be moderated by explicit sex role identification (Study 2, N = 1,831): the more women described themselves using traditionally masculine attributes (e.g., dominance, independence) relative to traditionally feminine attributes (e.g., warmth, tenderness), the more deliberation reduced their altruism. Our findings shed light on the connection between gender and altruism, and highlight the importance of social heuristics in human prosociality.

Context:Relatively little is known about the factors shaping public attitudes toward obesity as a policy concern. This study examines whether individuals' beliefs about the causes of obesity affect their support for policies aimed at stemming obesity rates. This article identifies a unique role of metaphor-based beliefs, as distinct from conventional political attitudes, in explaining support for obesity policies.Methods: This article used the Yale Rudd Center Public Opinion on Obesity Survey, a nationally representative web sample surveyed from the Knowledge Networks panel in 2006/07 (N = 1,009). The study examines how respondents' demographic and health characteristics, political attitudes, and agreement with seven obesity metaphors affect support for sixteen policies to reduce obesity rates. Findings:Including obesity metaphors in regression models helps explain public support for policies to curb obesity beyond levels attributable solely to demographic, health, and political characteristics. The metaphors that people use to understand rising obesity rates are strong predictors of support for public policy, and their influence varies across different types of policy interventions. Conclusions:Over the last five years, the United States has begun to grapple with the implications of dramatically escalating rates of obesity. Individuals use metaphors to better understand increasing rates of obesity, and obesity metaphors are independent and powerful predictors of support for public