The statistic shows the public opinion on the stereotyping of selected groups in movies and television in the United States as of February 2019. During the survey, 44 percent of respondents stated that the roles in American TV and movies were often stereotypes for Black people, and 31 percent said the same about the way in which LGBTQ people are represented.

A recent survey found that 58 percent of American TV content viewers feel that the media, regarding both news and entertainment, reinforces harmful stereotypes about diverse people in the United States. An even greater proportion felt that the media has a responsibility to undermine these stereotypes, with 68 percent of respondents reporting that it is important for the media to represent the diversity in American communities.

According to a recent survey, certain stereotypes about women still seem to be widespread among the G7 countries. Indeed, 41 percent of the respondents agreed the female brain is different from the male brain, which supposedly explains why men tend to have more aptitudes in certain subjects and women in others.

We gathered data from 2.162 Dutch high school students, after (pre-registered) exclusion criteria 2.064 students remained. Responses of those 2.064 students are included in the stored dataset. With this data we test the theory that gender stereotypes can lead to deteriorated math performance for female students, but not for male students. Students participated in an experiment: Students in the experimental condition were exposed to stereotype threat, for students in the control condition stereotype threat was removed. After the manipulation students finished a math test. The main research question is whether the four groups (experimental condition x gender) differ in performance on the math test. DSA proof. - Method: Collected at 21 Dutch high schools in Noord-Brabant, Zuid-Holland, Utrecht, and Overijssel. Data was collected with paper and pencil. - Universe: Dutch high school students from 2HAVO/VWO (age 13-14), in provinces Noord-Brabant, Zuid-Holland, Utrecht, and Overijssel.

This statistic illustrates the most widespread stereotypes about women according to a survey among the Italian adult population in 2018. According to data, the most common stereotypes about women were that they were better suited for child-rearing (63 percent of respondents), that they loved shopping (63 percent) and that they should take care of housework (59 percent).

Stereotypes are generalizations made about people based on their group membership. There is a wealth of literature examining the ways stereotypes contribute to the demonization of marginalized communities, impede communication, and permeate social structures. However, insufficient attention is directed towards the potential evolutionary benefit of stereotyping. Macrae et al. (1994) found that stereotypes may “free up” cognitive resources, which enables attention to be directed towards other essential functions. This paper has been cited over 1,700 times despite potential limitations including the small and homogeneous sample size, study and stereotype labels’ age, and failure to consider an alternative explanation; namely that labels, stereotypes or not, provide additional cognitive clues. Our research aims to replicate and extend Macrae et al. (1994)’s study to test whether stereotyping frees cognitive resources for diversion towards alternative tasks.

Women are extremely underrepresented in Japanese political life. One possible reason for this is that voters are biased against women. Compared to American voters, to what extent are Japanese voters opposed to women political leaders? What kinds of stereotypes do they have about women politicians? To answer these questions and probe the external validity of American studies on this topic, we conducted a survey that elicits respondents’ attitudes toward women political leaders. First, our list experiment outcomes revealed that approximately 10% of Japanese, and 20% of the Liberal Democratic Party (LDP) supporters, oppose a woman becoming prime minister. Second, we also identified respondents’ gender stereotypes by asking them directly about their impressions of politicians, which revealed that Japanese voters have strong stereotypes for men and women politicians regarding their policy areas of expertise and personal characteristics. These stereotypes are strongest among men and older voters as well as voters who support the LDP. Our findings have broad implications for the literature on gender and politics beyond the study of Japanese politics.

These are data from the primary dependent measures from my ESRC grant examining how intergoup bias influences the formation of novel lab-based stereotypes via a process of cumulative cultural evolution. The data were collected from undergraduate participants who were tested individually. Each participant was a single 'generation' within a 'diffusion chain' of four generations. Participants were asked to try and learn some information about some novel social targets. The responses each participant produced during a test phase were used as the learning materials for the next participant (i.e., generation). The dependent measures of interest were the accuracy with which people completed the task and the amount of structure that was present in their responses. We were interested in whether a stereotype-like categorical structure would develop as information was passed down the chains and whether this would result in associated increases in accuracy.

The proposed research will establish how the membership and status of social groups influences how cultural stereotypes form and change. Cultural stereotypes are template-like depictions of social categories whereby group membership is associated with the possession of certain attributes (e.g., scientists are geeky, Scottish people are miserly, men like the colour blue). Stereotypes exert substantial influence on us as individuals and on our society: when people endorse stereotypes it leads to prejudice and discrimination towards members of minority groups; even when people refute stereotypes the mere knowledge of their content can lead to unconscious bias in thoughts and behaviour. Yet, in the face of an infinitely complex social environment stereotypes play a vital social cognitive role by efficiently organising and structuring social information. Given their ubiquity and influence it is perhaps surprising that relatively little is known about how cultural stereotypes form and change.

We propose that stereotypes form and change via a process of cumulative cultural evolution. Because people possess shared biases that influence how information is remembered and communicated, when knowledge is repeatedly passed from person to person these biases accumulate causing the content of information to change in predictable ways. Research has shown that when information is passed down chains of individuals - a bit like the children's game often called 'Chinese whispers' or 'telephone' - it becomes increasingly simplified and structured. For example, we recently demonstrated that as novel social information passes from person to person it develops a stereotype-like structure that was not previously present. Thus, through the process of cumulative cultural evolution, even very small amounts of bias at the level of individual people can translate into much bigger societal biases like cultural stereotypes.

The proposed research will establish whether individual biases associated with a person's membership of social groups influences the formation and evolution of cultural stereotypes. Whether we perceive others as belonging to the same social group as ourselves (the in-group) or a different social group (the out-group) has profound implications for our thoughts and behaviours. Group membership tends to lead to intergroup bias, with people more likely to favour in-group members and discriminate against out-group members. The proposed research will determine whether repeatedly communicating social information about in-group and out-group members results in the formation of relatively positive in-group stereotypes and negative out-group stereotypes. In addition, the proposed research will also establish whether it is possible to predict how the content of stereotypes will evolve based on the perceived status of different out-groups (e.g., whether they are perceived to be high status or low status).

The proposed research will therefore help establish whether cumulative cultural evolution leads to the unintentional but inevitable formation of stereotypes, whose content is largely determined by the shared biases of perceivers rather than the actual properties of the groups themselves.

Raw data from Studies 1 & 2 from Numbers et al. JARMAC submission (under review). Data files contain false and veridical recall and recognition data, as well as post experimental questionnaire data. Accuracy proportions for Study 1 are 0%, 33% and 100% false, and confederate age conditions are young and old. Accuracy proportions for Study 2 are 0% and 100% false, and age stereotype conditions are positive and negative.

Stereotypes are encountered every day, in interpersonal communication as well as in entertainment, news stories, and on social media. In this study, we present a computational method to mine large, naturally occurring datasets of text for sentences that express perceptions of a social group of interest, and then map these sentences to the two-dimensional plane of perceived warmth and competence for comparison and interpretation. This framework is grounded in established social psychological theory, and validated against both expert annotation and crowd-sourced stereotype data. Additionally, we present two case studies of how the model might be used to answer questions using data “in-the-wild,” by collecting Twitter data about women and older adults. Using the data about women, we are able to observe how sub-categories of women (e.g., Black women and white women) are described similarly and differently from each other, and from the superordinate group of women in general. Using the data about older adults, we show evidence that the terms people use to label a group (e.g., old people vs. senior citizens) are associated with different stereotype content. We propose that this model can be used by other researchers to explore questions of how stereotypes are expressed in various large text corpora.

Edit 0_main.do to adjust the default path to the base replication folder.Add all ado files to the relevant STATA folderRun 0_main.do to replicate the main and appendix tables and figures of the paper.

The survey shows result of survey on stereotyping of racial minorities in Hollywood movies in the United States as of February 2016. The results were split my respondents' ethnicity. During the survey, 16 of Afrian American respondents stated Hollywood movies did a good job of potraying racial minorities.

One of the best-known empirical findings in the political sciences is the gender difference in political knowledge: women show less political knowledge than men. Conventional research argues that this difference is mainly a product of socialization, structural factors, and biology. Our paper brings a new perspective to the explanation of the gender gap in political knowledge. Based on an online survey and an experiment, we emphasize the relevance of gender stereotypes as a situational pressure that reduces the performance of women in a political knowledge test. Two conclusions emerge from the analysis: First, our results indicate the existence of a negative stereotype related to the political knowledge of women. Second, the activation of gender stereotypes affects performance on a political knowledge test. Consistent with previous research on stereotype threat, our results indicate that the performance of men on a political knowledge test is affected by gender stereotypes.

According to a survey conducted in September 2023, 70 percent of female respondents aged 15 to 19 years old stated that they preferred to be feminine, the highest share among women in Japan. For men, the share who desired to act masculine was highest among the oldest age group.

No description was included in this Dataset collected from the OSF

This contains the derivative data and code to create the figures and tables used in the paper. The data files contain derivative data based on raw data provided by DonorsChoose.org and available via data.donorschoose.org. The code includes an R file that combines the disparate data sets into a single data frame and produces the final analysis. There is also an R file containing functions which were not used to make figures or tables in the final paper, but are used in some analyses mentioned in the paper.

Two studies investigated whether interpretations of quantitative expressions about described actors’ behaviors are influenced by stereotypic expectancies. In two online experiments (one in Dutch language, and a direct replication in English language), participants were presented with sentences containing frequency adverbs describing either stereotype-consistent or stereotype-inconsistent behaviors. They rated perceived frequency of the described behaviors. Results showed that recipients inferred a higher numerical frequency when behaviors were stereotype consistent (vs inconsistent) for the described actors. These effects of stereotype consistency were stronger for high (vs low) degree frequency adverbs. The findings show how neutral statements about a person can be interpreted as stereotype-confirming information, which, in turn, may contribute to stereotype use and maintenance.

Keywords: linguistic bias, frequency adverbs, stereotypes, prejudice, language

This is a data package for our 2005 article in JPSP entitled Stereotype Threat and Group Differences in Test Performance: A Question of Measurement Invariance

Replication data. Visit https://dataone.org/datasets/sha256%3A13b6a85cb7c5221d82f93ef8dda00eb3c790e367429ef38e537fceb0123fa287 for complete metadata about this dataset.

Data analyzed in the Education and Information Technologies article, "Stereotype threat in Gamified Learning Environments]{Does Gender Stereotype Threat Affects the Levels of Aggressiveness, Learning and Flow in Gamified Learning Environments?: An Experimental Study"