Implicit Measures of Social Cognition

By Nilanjana Dasgupta. 2010

118 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/92df2db062ae82b149be3d11bd8a72cb92e53507

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Bertram Gawronski
2. Mandy Hütter
3. Karl Christoph Klauer
4. T. Langer
5. H. Blank
6. C. Pereira
7. Cheryl R. Kaiser
8. Cade Andrew McCall

In Social Psychology

1. Bertram Gawronski
2. B. Major
3. H. Blank
4. Karl Christoph Klauer
5. Mandy Hütter
6. E. Walther
7. T. Langer
8. Cheryl R. Kaiser

In Sociology and Political Science

1. Bertram Gawronski
2. B. Major
3. Cheryl R. Kaiser
4. P. Aguiar
5. C. Pereira
6. H. Blank
7. E. Walther
8. I. Correia

Citations in the corpus

• Justice in Our World and in that of Others: Belief in a Just World and Reactions to Victims (2008, methodology): “Then the threat to the BJW was measured using the emotional Stroop task developed by Hafer (2000), which directly assesses the threat to the participant’s BJW by comparing their performance on a task when colored stimuli are preceded by subliminally presented justice-related versus neutral words.”
• Mixed Signals: The Unintended Effects of Diversity Initiatives (2019, background): “Research assessing changes in implicit bias may alleviate some of these concerns, as measures of implicit bias are less susceptible to demand characteristics and are less under individual control (Fazio & Olson, 2003; Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005).”
• Applying processing trees in social psychology (2016, background): “The difference in response latencies between these two types of conditions serves as an indicator of spontaneously activated associations in memory that can differ markedly from explicit evaluations obtained on selfreport measures (Fazio & Olson, 2003; Wilson et al., 2000).”
• Changing likes and dislikes through the back door: The US-revaluation effect (2009, background): “Because affective priming should be less prone to the type of response biases often obtained in self-report measures (Fazio & Olson, 2003), these findings indicate that the US-revaluation effect is not due to simple demand characteristics.”
• Proxemic behaviors as predictors of aggression towards Black (but not White) males in an immersive virtual environment (2009, background): “This discrepancy has motivated researchers to search for covert or implicit markers of racial attitudes, resulting in various priming and/or reaction time techniques (Fazio & Olson, 2003).”