Academic literature on the topic 'Bias and stereotypes'

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Journal articles on the topic "Bias and stereotypes"

1

Rivers, Andrew M., Jeffrey W. Sherman, Heather R. Rees, Regina Reichardt, and Karl C. Klauer. "On the Roles of Stereotype Activation and Application in Diminishing Implicit Bias." Personality and Social Psychology Bulletin 46, no. 3 (2019): 349–64. http://dx.doi.org/10.1177/0146167219853842.

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Stereotypes can influence social perception in undesirable ways. However, activated stereotypes are not always applied in judgments. The present research investigated how stereotype activation and application processes impact social judgments as a function of available resources for control over stereotypes. Specifically, we varied the time available to intervene in the stereotyping process and used multinomial modeling to independently estimate stereotype activation and application. As expected, social judgments were less stereotypic when participants had more time to intervene. In terms of mechanisms, stereotype application, and not stereotype activation, corresponded with reductions in stereotypic biases. With increasing time, stereotype application was reduced, reflecting the fact that controlling application is time-dependent. In contrast, stereotype activation increased with increasing time, apparently due to increased engagement with stereotypic material. Stereotype activation was highest when judgments were least stereotypical, and thus, reduced stereotyping may coincide with increased stereotype activation if stereotype application is simultaneously decreased.
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2

Skorinko, Jeanine Lee McHugh. "Riddle Me This: Using Riddles That Violate Gender Stereotypes To Demonstrate The Pervasiveness Of Stereotypes." Psychology Learning & Teaching 17, no. 2 (2018): 194–208. http://dx.doi.org/10.1177/1475725717752181.

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This paper describes a classroom demonstration that showcases how pre-existing beliefs (e.g., stereotypes) influence problem-solving. Across four studies, participants solved riddles with gender stereotype-consistent (e.g. doctor is male) or gender stereotype-inconsistent (e.g., doctor is female; barber is female) solutions. Solve time, perceived difficulty, and perceptions of the demonstration and how it influenced learning were measured. Studies 3 and 4 extended Studies 1 and 2 by measuring objective learning through a quiz on gender stereotypes and bias. Results indicate that students solved the stereotype-inconsistent riddles slower than stereotype-consistent riddles. Stereotype-inconsistent riddles were rated as more difficult to solve than stereotype-consistent riddles. Subjectively, participants perceived the demonstration to be an effective tool, enhancing their knowledge about gender stereotypes. Objectively, participants performed better on the quiz when they solved stereotype-inconsistent riddles than stereotype-consistent riddles. These findings suggest that using stereotype-inconsistent riddles in class can help understanding about gender stereotypes and bias.
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3

Heilman, Madeline E. "Gender stereotypes and workplace bias." Research in Organizational Behavior 32 (January 2012): 113–35. http://dx.doi.org/10.1016/j.riob.2012.11.003.

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4

Bye, Hege H., and Henrik Herrebrøden. "Emotions as mediators of the stereotype–discrimination relationship: A BIAS map replication." Group Processes & Intergroup Relations 21, no. 7 (2017): 1078–91. http://dx.doi.org/10.1177/1368430217694370.

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A central theoretical assumption in the Behaviors from Intergroup Affect and Stereotypes (BIAS) map framework is that emotions mediate the relationships between stereotypes and intergroup behavior. Despite the BIAS map’s popularity, very few studies have tested the model’s mediation hypotheses and none have tested them by replicating the original study (Cuddy, Fiske, & Glick, 2007, Study 1). We provide a replication in a Norwegian sample ( N = 244). The results supported that stereotype content is related to behavior tendencies, mediated through emotional prejudices. However, for each of the four behavior outcomes the effect of stereotype content was mediated through one emotion rather than two as predicted by the BIAS map. Our findings both converge and diverge from those of Cuddy and colleagues, and provide support for theoretical propositions unsupported by the original study. Overall, the study provides empirical support for the BIAS map framework and its cross-cultural validity.
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5

Moons, Wesley G., Jacqueline M. Chen, and Diane M. Mackie. "Stereotypes: A source of bias in affective and empathic forecasting." Group Processes & Intergroup Relations 20, no. 2 (2016): 139–52. http://dx.doi.org/10.1177/1368430215603460.

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People’s emotional states often depend on the emotions of others. Consequently, to predict their own responses to social interactions (i.e., affective forecasts), we contend that people predict the emotional states of others (i.e., empathic forecasts). We propose that empathic forecasts are vulnerable to stereotype biases and demonstrate that stereotypes about the different emotional experiences of race (Experiment 1) and sex groups (Experiment 2) bias empathic forecasts. Path modeling in both studies demonstrates that stereotype-biased empathic forecasts regarding how a target individual will feel during a social interaction are associated with participants’ affective forecasts of how they will feel during that interaction with the target person. These affective forecasts, in turn, predict behavioral intentions for the social interaction before it even begins. Stereotypes can therefore indirectly bias affective forecasts by first influencing the empathic forecasts that partly constitute them. In turn, these potentially biased affective forecasts determine social behaviors.
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Grant, Sharon, and Toby Mizzi. "Body Weight Bias in Hiring Decisions: Identifying Explanatory Mechanisms." Social Behavior and Personality: an international journal 42, no. 3 (2014): 353–70. http://dx.doi.org/10.2224/sbp.2014.42.3.353.

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We examined the impact of job applicant body weight on employability ratings via the mediators of obesity and physical attractiveness stereotypes, organizational costs, and rational bias. The moderating effect of job type was also examined. A sample of 202 (75% female) university students assessed a job applicant on the basis of a résumé which was accompanied by a photograph (overweight vs. average weight) and a position description (face-to-face vs. telephone sales). Results revealed that the overweight applicant was rated significantly higher on the obesity stereotype, significantly lower on the physical attractiveness stereotype, and as significantly less employable. Stereotypes failed to mediate between applicant weight and employability, and rational bias only was found to be a significant mediator. There was no significant interaction between applicant weight and job type when the mediators were controlled. Our findings in this study underscore the importance of examining multiple pathways from applicant weight to employment-related weight discrimination.
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7

Fiebert, Martin S., and Mark W. Meyer. "Gender Stereotypes: A Bias Against Men." Journal of Psychology 131, no. 4 (1997): 407–10. http://dx.doi.org/10.1080/00223989709603527.

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8

Carlana, Michela. "Implicit Stereotypes: Evidence from Teachers’ Gender Bias*." Quarterly Journal of Economics 134, no. 3 (2019): 1163–224. http://dx.doi.org/10.1093/qje/qjz008.

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Abstract I study whether exposure to teacher stereotypes, as measured by the Gender-Science Implicit Association Test, affects student achievement. I provide evidence that the gender gap in math performance, defined as the score of boys minus the score of girls in standardized tests, substantially increases when students are assigned to math teachers with stronger gender stereotypes. Teacher stereotypes induce girls to underperform in math and self-select into less demanding high schools, following the track recommendation of their teachers. These effects are at least partially driven by lower self-confidence on math ability of girls exposed to gender-biased teachers. Stereotypes impair the test performance of girls, who end up failing to achieve their full potential. I do not detect statistically significant effects on student outcomes of literature teacher stereotypes.
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9

Villicana, Adrian J., Donna M. Garcia, and Monica Biernat. "Gender and parenting: Effects of parenting failures on evaluations of mothers and fathers." Group Processes & Intergroup Relations 20, no. 6 (2015): 867–78. http://dx.doi.org/10.1177/1368430215615683.

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Stereotypes may function as standards, such that individuals are judged relative to within-category expectations. Subjective judgments may mask stereotyping effects, whereas objective judgments may reveal stereotype-consistent patterns. We examined whether gender stereotypes about parenting lead judges to rate women and men as equally “good” parents while objective judgments favor women and whether parenting performance moderates this pattern. Participants evaluated a mother or father who successfully or unsuccessfully performed a parenting task. Subjective judgments of parent quality (“s/he is a good parent”) revealed no parent gender effects, but objective estimates of parenting performance favored mothers. In a hypothetical divorce scenario, participants also favored mothers in custody decisions. However, this pro-mother bias decreased when the mother failed at the parenting task (through her own fault). Performance did not affect custody decisions for fathers. We suggest parenting quality matters more for evaluations of mothers than for fathers because negative performance violates stereotyped expectations.
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10

Sánchez-Junquera, Javier, Berta Chulvi, Paolo Rosso, and Simone Paolo Ponzetto. "How Do You Speak about Immigrants? Taxonomy and StereoImmigrants Dataset for Identifying Stereotypes about Immigrants." Applied Sciences 11, no. 8 (2021): 3610. http://dx.doi.org/10.3390/app11083610.

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Stereotype is a type of social bias massively present in texts that computational models use. There are stereotypes that present special difficulties because they do not rely on personal attributes. This is the case of stereotypes about immigrants, a social category that is a preferred target of hate speech and discrimination. We propose a new approach to detect stereotypes about immigrants in texts focusing not on the personal attributes assigned to the minority but in the frames, that is, the narrative scenarios, in which the group is placed in public speeches. We have proposed a fine-grained social psychology grounded taxonomy with six categories to capture the different dimensions of the stereotype (positive vs. negative) and annotated a novel StereoImmigrants dataset with sentences that Spanish politicians have stated in the Congress of Deputies. We aggregate these categories in two supracategories: one is Victims that expresses the positive stereotypes about immigrants and the other is Threat that expresses the negative stereotype. We carried out two preliminary experiments: first, to evaluate the automatic detection of stereotypes; and second, to distinguish between the two supracategories of immigrants’ stereotypes. In these experiments, we employed state-of-the-art transformer models (monolingual and multilingual) and four classical machine learning classifiers. We achieve above 0.83 of accuracy with the BETO model in both experiments, showing that transformers can capture stereotypes about immigrants with a high level of accuracy.
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