In this accessible and groundbreaking look at the science of prejudice, Banaji and Greenwald show that prejudice and unconscious biases toward others are a fundamental part of the human psyche.

We study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-American- or White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to still be prominent in the U. S. labor market.

America may be more diverse than ever coast to coast, but the places where we live are becoming increasingly crowded with people who live, think, and vote as we do. We've built a country where we can all choose the neighborhood--and church and news show--most compatible with our lifestyle and beliefs. And we are living with the consequences of this way-of-life segregation. Our country has become so polarized, so ideologically inbred, that people don't know and can't understand those who live just a few miles away. The reason for this situation, and the dire implications for our country, is the subject of this groundbreaking work.

Gender equality is a moral and a business imperative. But unconscious bias holds us back and de-biasing minds has proven to be difficult and expensive. Behavioral design offers a new solution. Iris Bohnet shows that by de-biasing organizations instead of individuals, we can make smart changes that have big impacts--often at low cost and high speed.

Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates—with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, social science) than in the math-intensive fields in which they are underrepresented but in which the number of females holding assistant professorships is at least commensurate with (if not greater than) that of males. That is, invitations to interview for tenure-track positions in math-intensive fields—as well as actual employment offers—reveal that female PhD applicants fare at least as well as their male counterparts in math-intensive fields. Along these same lines, our analyses reveal that manuscript reviewing and grant funding are gender neutral: Male and female authors and principal investigators are equally likely to have their manuscripts accepted by journal editors and their grants funded, with only very occasional exceptions. There are no compelling sex differences in hours worked or average citations per publication, but there is an overall male advantage in productivity. We attempt to reconcile these results amid the disparate claims made regarding their causes, examining sex differences in citations, hours worked, and interests. We conclude by suggesting that although in the past, gender discrimination was an important cause of women’s underrepresentation in scientific academic careers, this claim has continued to be invoked after it has ceased being a valid cause of women’s underrepresentation in math-intensive fields. Consequently, current barriers to women’s full participation in mathematically intensive academic science fields are rooted in pre-college factors and the subsequent likelihood of majoring in these fields, and future research should focus on these barriers rather than misdirecting attention toward historical barriers that no longer account for women’s underrepresentation in academic science.

People can make decisions to join a group based solely on exposure to that group’s physical environment. Four studies demonstrate that the gender difference in interest in computer science is influenced by exposure to environments associated with computer scientists. In Study 1, simply changing the objects in a computer science classroom from those considered stereotypical of computer science (e.g., Star Trek poster, video games) to objects not considered stereotypical of computer science (e.g., nature poster, phone books) was sufficient to boost female undergraduates’ interest in computer science to the level of their male peers. Further investigation revealed that the stereotypical broadcast a masculine stereotype that discouraged women’s sense of ambient belonging and subsequent interest in the environment (Studies 2, 3, and 4) but had no similar effect on men (Studies 3, 4). This masculine stereotype prevented women’s interest from developing even in environments entirely populate

The concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analysis of dropouts from high school. The conception of social capital as a resource for action is one way of introducing social structure into the rational action paradigm. 3 forms of social capital are examined: obligations and expectations, information channels, and social norms.

Historically, there has been a strong connection between increasing educational attainment in the United States and the growth in and global leadership of the economy. Consequently, there have been calls—from the College Board, the Lumina and Gates Foundations, and the administration—to increase the postsecondary completion rate in the United States from 39 percent to 55 or 60 percent. The challenge is greatest for underrepresented minorities: In 2006 only 26 percent of African Americans, 18 percent of American Indians, and 16 percent of Hispanics in the 25- to 29-year-old cohort had attained at least an associate degree. The news is even worse in S&E (science and engineering) fields. In 2000, as noted in Gathering Storm, the United States ranked 20 out of 24 countries in the percentage of 24-year-olds who had earned a first degree in the natural sciences or engineering. Based on these data, Gathering Storm recommended efforts to increase the percentage of 24-year-olds with these degrees from 6 percent to at least 10 percent, the benchmark already attained by several countries. But again, the statistics are even more alarming for underrepresented minorities. These students would need to triple, quadruple, or even quintuple their proportions with a first university degree in these fields in order to achieve this 10 percent goal: At present, just 2.7 percent of African Americans, 3.3 percent of Native Americans and Alaska Natives, and 2.2 percent of Hispanics and Latinos who are 24 years old have earned a first university degree in the natural sciences or engineering.

Psychologists have demonstrated the value of diversity – particularly diversity of viewpoints – for enhancing creativity, discovery, and problem solving. But one key type of viewpoint diversity is lacking in academic psychology in general and social psychology in particular: political diversity. This article reviews the available evidence and finds support for four claims: (1) Academic psychology once had considerable political diversity, but has lost nearly all of it in the last 50 years. (2) This lack of political diversity can undermine the validity of social psychological science via mechanisms such as the embedding of liberal values into research questions and methods, steering researchers away from important but politically unpalatable research topics, and producing conclusions that mischaracterize liberals and conservatives alike. (3) Increased political diversity would improve social psychological science by reducing the impact of bias mechanisms such as confirmation bias, and by empowering dissenting minorities to improve the quality of the majority's thinking. (4) The underrepresentation of non-liberals in social psychology is most likely due to a combination of self-selection, hostile climate, and discrimination. We close with recommendations for increasing political diversity in social psychology.