52% Yes, a signiicant crisis 3% No, there is no crisis 7% Don't know 38% Yes, a slight crisis 38% Yes, a slight crisis 1,576 RESEARCHERS SURVEYED M ore than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments. Those are some of the telling figures that emerged from Nature's survey of 1,576 researchers who took a brief online questionnaire on reproducibility in research. The data reveal sometimes-contradictory attitudes towards reproduc-ibility. Although 52% of those surveyed agree that there is a significant 'crisis' of reproducibility, less than 31% think that failure to reproduce published results means that the result is probably wrong, and most say that they still trust the published literature. Data on how much of the scientific literature is reproducible are rare and generally bleak. The best-known analyses, from psychology 1 and cancer biology 2 , found rates of around 40% and 10%, respectively. Our survey respondents were more optimistic: 73% said that they think that at least half of the papers in their field can be trusted, with physicists and chemists generally showing the most confidence. The results capture a confusing snapshot of attitudes around these issues, says Arturo Casadevall, a microbiologist at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. "At the current time there is no consensus on what reproducibility is or should be. " But just recognizing that is a step forward, he says. "The next step may be identifying what is the problem and to get a consensus. "
Many methods for reducing implicit prejudice have been identified, but little is known about their relative effectiveness. We held a research contest to experimentally compare interventions for reducing the expression of implicit racial prejudice. Teams submitted seventeen interventions that were tested an average of 3.70 times each in four studies (total N = 17,021), with rules for revising interventions between studies. Eight of seventeen interventions were effective at reducing implicit preferences for Whites compared to Blacks, particularly ones that provided experience with counterstereotypical exemplars, used evaluative conditioning methods, and provided strategies to override biases. The other nine interventions were ineffective, particularly ones that engaged participants with others' perspectives, asked participants to consider egalitarian values, or induced a positive emotion. The most potent interventions were ones that invoked high self-involvement or linked Black people with positivity and White people with negativity. No intervention consistently reduced explicit racial preferences. Furthermore, intervention effectiveness only weakly extended to implicit preferences for Asians and Hispanics. Abstract = 160 words Keywords = attitudes, racial prejudice, implicit social cognition, malleability, Implicit Association Test September 9, 2016 update: We updated this manuscript to fix several minor reporting errors that we have learned about since the publication of the manuscript in August 2014. For a summary of these updates, please see pages 67 and 68. Authors' note:This project was supported by a gift from Project Implicit. Lai and Hawkins are consultants and Nosek is an officer of Project Implicit, Inc., a non-profit organization that includes in its mission "To develop and deliver methods for investigating and applying phenomena of implicit social cognition, including especially phenomena of implicit bias based on age, race, gender or other factors. Thoughts and feelings outside of conscious awareness shape social perception, judgment and action (Bargh, 1999;Devine, 1989;Greenwald & Banaji, 1995). Nowhere has this idea been more explored than in studies of racial prejudice in which people report egalitarian racial attitudes, but also implicitly prefer Whites compared to Blacks (Devine, 1989;Dovidio, Kawakami, Johnson, Johnson, & Howard, 1997;Fazio, Jackson, Dunton, & Williams, 1995;. These studies have been influential because implicit racial preferences predict behaviors such as negative interracial contact (McConnell & Leibold, 2001), biases in medical decision-making (Green et al., 2007), and hiring discrimination (Rooth, 2010).From the hundreds of studies conducted, we can conclude that implicit preferences (1) are related to, but distinct from, explicit preferences (Greenwald & Banaji, 1995;, (2) are constructed through different mechanisms than explicit preferences (De Houwer, Teige-Mocigemba, Spruyt, & Moors, 2009;Ranganath & Nosek, 2008;Ratliff & Nosek, 2011;Rydell & McConnell, 2006), ...
Most of human cognition occurs outside of conscious awareness or conscious control. Some of these implicit processes influence social perception, judgment and action. The last fifteen years of research in implicit social cognition can be characterized as the Age of Measurement because of a proliferation of measurement methods and research evidence demonstrating their practical value for predicting human behavior. Implicit measures assess constructs that are distinct, but related, to self-report assessments, and predict variation in behavior that is not accounted for by those explicit measures. The present state of knowledge provides a foundation for the next age of implicit social cognition – clarification of the mechanisms underlying implicit measurement and how the measured constructs influence behavior.
Number of citations and the h-index are popular metrics for indexing scientific impact. These, and other existing metrics, are strongly related to scientists' seniority. This article introduces complementary indicators that are unrelated to the number of years since PhD. To illustrate cumulative and career-stage approaches for assessing the scientific impact across a discipline, citations for 611 scientists from 97 U.S. and Canadian social psychology programs are amassed and analyzed. Results provide benchmarks for evaluating impact across the career span in psychology and other disciplines with similar citation patterns. Career-stage indicators provide a very different perspective on individual and program impact than cumulative impact, and may predict emerging scientists and programs. Comparing social groups, Whites and men had higher impact than non-Whites and women, respectively. However, average differences in career stage accounted for most of the difference for both groups.
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