Implicit stereotyping - research Flashcards
Greenwald and Banaji (1995)
Much social cognition occurs in an implicit mode. This conclusion comes from a reinterpretation of many findings that indicate the importance of implicit operation of attitudes, and of the self-esteem attitude in particular, and also from existing and new evidence for the implicit operation of stereotypes. By adding this conception of the implicit mode to existing knowledge of the explicit mode of operation of social psychology’s basic constructs, the scope of those constructs is extended substantially. In addition, many possibilities for application in decision making settings are suggested by interpreting social judgment in terms of an interaction of implicit and explicit social cognition.
Implicit social cognition overlaps with several concepts that were significant in works of previous generations of psychologists. Psychoanalytic theory’s concept of cathexis contained some of the sense of implicit attitude, and its concept of ego defense similarly captured at least part of the present notion of implicit self-esteem. Partly under the influence of psychoanalytic theory, in the 1930s and 1940s, attitudes were regarded as capable of unconscious operation. The authoritarian personality concept (Adorno, Frenkel-Brunswik, Levinson, & Sanford, 1950) extended the psychoanalytic approach to include social phenomena of prejudice and stereotyping. At a time when the
influence of psychoanalytic theory in academic psychology was declining, its conceptions of unconscious phenomena that related to implicit social cognition were being imported into behavior theory (Dollard & Miller, 1950; Doob, 1947; Osgood, 1957). The New Look in Perception of the 1950s focused on several phenomena that are interpretable as implicit social cognition. The developing cognitive approach to these phenomena can be seen in Bruner’s (1957) introduction of the concept of
perceptual readiness. Still later, the New Look approach was tied together with psychoanalytic theoretical influences in a cognitive-psychological account by Erdelyi (1974, 1985).
Importantly, the psychoanalytic, behaviorist, and cognitive
treatments just mentioned all lacked an essential ingredient, that is, they lacked reliable laboratory models of their focal phenomena that could support efficient testing and development of theory. The missing ingredient is now available, as cognitive psychologists have succeeded in producing several varieties of unconscious cognition reliably in the laboratory (see overviews
by Greenwald, 1992a; Kihlstrom, 1987), and investigations of implicit social cognition are well underway (see Bornstein & Pittman, 1992; Uleman & Bargh, 1989). The methods of research on implicit memory, in particular, are applicable to the implicit attitude, self-esteem, and stereotype phenomena reviewed in this article. Perhaps the most significant remaining challenge is to adapt these methods for efficient ass
Hugenberg and Bodenhausen (2003)
We propose that social attitudes, and in particular implicit
prejudice, bias people’s perceptions of the facial emotion displayed by others. To test this hypothesis, we employed a facial emotion changedetection task in which European American participants detected the offset (Study 1) or onset (Study 2) of facial anger in both Black and White targets. Higher implicit (but not explicit) prejudice was associated with a greater readiness to perceive anger in Black faces, but neither explicit nor implicit prejudice predicted anger perceptions regarding similar White faces. This pattern indicates that European Americans high in implicit racial prejudice are biased to perceive threatening affect in Black but not White faces, suggesting that the deleterious effects of stereotypes may take hold extremely early in social interaction.
Forscher et al. (2019)
implicit measured can be changed but effects weak
studies focus on producing short term changes
associating goals, concepts and motives changed implicit measures the most
changing implicit measures doesn’t always translate into changing explicit measures
Carlana (2019)
teacher stereotypes cause girls to underperform and select less demanding schools
driven by lower self-confidence
impair test performance
Maina et al. (2018)
Synthesizes the current literature on the use of the IAT in healthcare providers.
37 studies demonstrate mixed results for the role of implicit bias in disparities.
Increased provider bias consistently correlates with poorer patient-provider interactions.
Leuke and Gibson (2014)
mindfulness helps people rely less on established associations
implicit age and racial bias
mindfulness/control audio
decrease in implicit race and age bias
weaker activation of associations
Druckman et al. (2018)
Injured student-athletes rely on university medical staff personnel for care. Do these practitioners exhibit race and/or gender biases in their perceptions of injured student-athletes? While such biases have been widely documented in other medical practitioner populations, they have not been studied in the domain of college athletics. We use a survey experiment conducted on National Collegiate Athletic Association Division 1 medical staff to explore perceptions of an injured student-athlete (e.g. the likelihood of the student-athlete complying with treatment). We find little evidence of bias. We discuss why this population of medical practitioners may differ from others, and we offer suggestions for future work on medical treatment of student-athletes.
Marini et al. (2018)
anterior temporal lobe crucial area for representation of implicit stereotypes
processing of implicit attitudes requires the inferior parietal lobe
the medial PFC can change the expression of implicit stereotypes
Hall et al. (2015)
Main Results. Almost all studies used cross-sectional designs, convenience sampling, US participants, and the Implicit Association Test to assess implicit bias. Low to moderate levels of implicit racial/ethnic bias were found among health care professionals in all but 1 study. These implicit bias scores are similar to those in the general population. Levels of implicit bias against Black, Hispanic/Latino/Latina, and dark-skinned people were relatively similar across these groups. Although some associations between implicit bias and health care outcomes were nonsignificant, results also showed that implicit bias was significantly related to patient–provider interactions, treatment decisions, treatment adherence, and patient health outcomes. Implicit attitudes were more often significantly related to patient–provider interactions and health outcomes than treatment processes.
Conclusions. Most health care providers appear to have implicit bias in terms of positive attitudes toward Whites and negative attitudes toward people of color. Future studies need to employ more rigorous methods to examine the relationships between implicit bias and health care outcomes. Interventions targeting implicit attitudes among health care professionals are needed because implicit bias may contribute to health disparities for people of color.
Gawronski (2019)
Skepticism about the explanatory value of implicit bias in understanding social discrimination has grown considerably. The current article argues that both the dominant narrative about implicit bias as well as extant criticism are based on a selective focus on particular findings that fails to consider the broader literature on attitudes and implicit measures. To provide a basis to move forward, the current article discusses six lessons for a cogent science of implicit bias: (a) There is no evidence that people are unaware of the mental contents underlying their implicit biases; (b) conceptual correspondence is essential for interpretations of dissociations between implicit and explicit bias; (c) there is no basis to expect strong unconditional relations between implicit bias and behavior; (d) implicit bias is less (not more) stable over time than explicit bias; (e) context matters fundamentally for the outcomes obtained with implicit-bias measures; and (f) implicit measurement scores do not provide process-pure reflections of bias. The six lessons provide guidance for research that aims to provide more compelling evidence for the properties of implicit bias. At the same time, they suggest that extant criticism does not justify the conclusion that implicit bias is irrelevant for the understanding of social discrimination.
Paulus and Wentura (2018)
Faces carry a lot of information influencing evaluative reactions, such as emotional expression, age, or group membership. Even though, typically, many of these aspects will be present in a face concurrently, only few studies have examined automatic evaluative reactions to faces that vary on more than one dimension. As an exception, two recent priming studies examined the concurrent influence of group membership and emotional expression. Quite astoundingly, they leave the reader with two divergent outcomes: while Weisbuch and Ambady (2008) observed an interactive influence of emotional expression and group membership on evaluative reactions, Craig et al. (2014) found that group membership did not contribute to the implicit evaluation of positive and negative emotional expressions. In order to shed light on this matter, we conducted three high-powered experiments using prime images of highly relevant in-group and out-group members expressing happiness and fear. We furthermore varied the social context of the priming task in order to give the “interaction hypothesis” a chance. However, we found no evidence for the interaction reported by Weisbuch and Ambady. In contrast to Craig et al., we found that both emotional expression and group membership independently contributed to implicit evaluations. Differences are discussed in terms of relevance of the employed groups, test power, and the time-scale of underlying processes.
Greenwald et al. (2015)
Greenwald, Poehlman, Uhlmann, and Banaji (2009; GPUB hereafter) reported an average predictive validity correlation of r̄ = .236 for Implicit Association Test (IAT) measures involving Black–White racial attitudes and stereotypes. Oswald, Mitchell, Blanton, Jaccard, and Tetlock (2013; OMBJT) reported a lower aggregate figure for correlations involving IAT measures (r̄ = .148). The difference between the estimates of the 2 reviews was due mostly to their use of different policies for including effect sizes. GPUB limited their study to findings that assessed theoretically expected attitude–behavior and stereotype–judgment correlations along with others that the authors expected to show positive correlations. OMBJT included a substantial minority of correlations for which there was no theoretical expectation of a predictive relationship. Regardless of inclusion policy, both meta-analyses estimated aggregate correlational effect sizes that were large enough to explain discriminatory impacts that are societally significant either because they can affect many people simultaneously or because they can repeatedly affect single persons.
