During the past 30 years, women’s participation in the workforce, in athletics, and in professional education has increased, while men’s activities have been more stable. Have gender stereotypes changed over this time period to reflect the new realities? And, to what extent does gender stereotyping exist today? We address these questions by comparing data collected in the early 1980s to new data collected in 2014. In each study, participants rated the likelihood that a typical man or woman has a set of gendered characteristics (traits, role behaviors, occupations, and physical characteristics). Results indicate that people perceive strong differences between men and women on stereotype components today, as they did in the past. Comparisons between the two time periods show stability of gender stereotypes across all components except female gender roles, which showed a significant increase in gender stereotyping. These results attest to the durability of basic stereotypes about how men and women are perceived to differ, despite changes in the participation and acceptance of women and men in nontraditional domains. Because gender stereotypes are apparently so deeply embedded in our society, those in a position to evaluate women and men, as well as women and men themselves, need to be constantly vigilant to the possible influence of stereotypes on their judgments, choices, and actions. Online slides for instructors who want to use this article for teaching are available on PWQ's website at http://pwq.sagepub.com/supplemental

Just as the invention of specific technologies dramatically changed the course of the older sciences, the Internet has the potential to transform what the behavioral, social, and mind sciences can accomplish in the 21 st century. Project Implicit represents a case study of a single modest effort in which, over the course of a decade, five million tests of implicit social cognition were administered to drop-in participants. From this experience, a broader interdisciplinary collaboration was initiated, providing a case example of using technical and methodological innovation for accelerating and enhancing scientific research. The project's Virtual Laboratory provides a nexus for research collaboration, a virtual workbench for developing and managing web-based research protocols, and a robust infrastructure for administering experiments. With collective effort, the Internet will transform the research process by fostering collaboration, expanding access to samples all over the globe, facilitating data integration, and enabling a common framework for scientific research. Abstract = 150 words Keywords = Internet, research methodology, measurement, experimental design, innovation, implicit cognition Virtual Laboratory 3More than researchers would care to admit, study design is guided by practical factors of what study design can be done, rather than how it should be done. In an ideal research world, a scientist would conceive a question, generate the best paradigm to test it, and then execute the study. The "perfect study," a mythical, Platonic ideal, is the

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Can people learn about implicit bias through an online course? We developed a brief (∼30 min) online educational program called Understanding Implicit Bias (UIB) consisting of four modules: (a) what is implicit bias? (b) the Implicit Association Test, (c) implicit bias and behavior, and (d) what can you do? In Experiment 1, we randomly assigned 6,729 college students across three separate samples to complete dependent measures before (control group) or after (intervention group) the UIB program. In Experiment 2, we randomly assigned 389 college students to complete the UIB program (intervention group) or two TED talks (control group) before dependent measures. Compared to control groups, the intervention groups had significantly higher objective knowledge about bias (ds = 0.39, 1.49) and subjective knowledge about bias (ds = 1.43, 2.61), awareness of bias (ds = 0.10, 0.54), and behavioral intentions to reduce bias (ds = 0.19, 0.84). These differences were again observed at a 2-week follow-up. These results suggest that brief online education about bias can affect knowledge and awareness of bias, as well as intentions to change behavior. Public Significance StatementThe Understanding Implicit Bias (UIB) program is a brief interactive online educational program to teach students about bias. Compared to control groups, the UIB program increases bias knowledge, awareness, and intentions to reduce bias in behavior.

For decades, researchers across the social sciences have sought to document and explain the worldwide variation in social group attitudes (evaluative representations, e.g., young-good/old-bad) and stereotypes (attribute representations, e.g., male–science/female–arts). Indeed, uncovering such country-level variation can provide key insights into questions ranging from how attitudes and stereotypes are clustered across places to why some places have stronger attitudes and stereotypes than others (including ecological and social correlates). Here, we introduce the Project Implicit:International (PI:International) dataset that uniquely propels this research forward by offering the first cross-country dataset of both implicit (indirectly-measured) and explicit (directly-measured) attitudes and stereotypes across multiple topics and years. Specifically, PI:International comprises 2.3 million tests for 7 topics (race, sexual orientation, age, body weight, nationality, and skin-tone attitudes, as well as men/women–science/arts stereotypes) using both indirect (Implicit Association Test; IAT) and direct (self-report) measures collected continuously from 2009 to 2019 from 36 country-specific websites in each country’s native language(s). We show that the IAT data from PI:International has adequate internal consistency (split-half reliability), convergent validity (implicit–explicit correlations), and known groups validity. Given such reliability and validity, we summarize basic descriptive results on the overall strength and variability of implicit and explicit attitudes and stereotypes around the world. The PI:International dataset, including both cleaned data and trial-level data from the IAT, is provided openly to facilitate wide access and novel discoveries on the global nature of implicit and explicit attitudes and stereotypes.