Publications by authors named "Nicole Lofaro"

This research tested whether institutional change impacts policy support and attitudes toward the social groups impacted by policy change. Study 1 demonstrated across a variety of topics that, when a hypothetical state legislature (vs. ) a practice (e.

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People who are more defensive about their feedback on the Race-Attitudes Implicit Association Test (IAT) are less willing to engage in anti-bias behaviors. Extending on this work, we statistically clarified defensiveness constructs to predict willingness to engage in anti-bias behaviors among people who received pro-White versus no-bias IAT feedback. We replicated the finding that U.

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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 (s = 0.

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In the current study we move away from bias-focused, White-centric research to examine relationships between gender, race/ethnicity, and weight-related attitudes, identity, and beliefs among Black, Black/White Biracial, East Asian, Hispanic/Latino, Native American, South Asian, and White U.S. Americans who self-identify as higher weight.

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Article Synopsis
  • Researchers have been studying how social group attitudes and stereotypes vary around the world, which helps us understand their patterns and the reasons behind these differences.
  • The Project Implicit:International (PI:International) dataset is a groundbreaking resource that includes 2.3 million tests from 34 countries, measuring implicit and explicit attitudes on topics like race, age, and gender-related stereotypes from 2009 to 2019.
  • The dataset demonstrates strong reliability and validity, offering comprehensive statistics on global attitudes and stereotypes, and is openly available for researchers to explore and make new discoveries.
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