Method

1. Hostile and Ambivalent Sexism: Exploring the world of stereotypes Jessica Chandler University of Nebraska-Lincoln Introduction Results As more research has begun to investigate people’s uses of stereotypes towards women we see that different levels of sexism exist. Much of stereotyping originates in the social construct of our society and things deemed acceptable for each sex. For example, in the history of the world women were valued for their maternal values, beauty and submissiveness and seen in a negative light for qualities considered masculine (Glick & Fiske, 1997). As for men they are valued for their strength, dominate nature, and ability to provide for women and qualities like sensitivity and emotionality are viewed as “sissy” for men. The characteristics people exude are what group people, and while these ideas of men and women are changing there are many that have stayed very much the same over the centuries. Status characteristics and social roles emphasize social structural factors that produce expectations about male and female behavior. It is easier to account for sex differences that are a result of social position, culture and gender norms (Carli & Eagly, 1999). These are very important factors that need to be included when dealing with gender, although biological factors play a part, social context may play a bigger role in behavior. These different levels of sexism play a part in how people interpret the incoming information in three forms hostile, ambivalent, and benevolent sexism. Hostile sexism is the standard form of stereotyping most people associate with sexism and is antipathy or hostility towards women and justifying male power, traditional gender roles, and men’s exploitation of women as sexual objects and prescribed gender roles (Glick & Fiske, 1997). Benevolent sexism, in contrast, is a much kinder and gentler view of women with feelings of protectiveness and affection for women, while still seeing them as the weaker sex (Glick & Fiske, 1997). Ambivalent sexism encompasses both aspects of benevolent and hostile. This idea can be further understood by saying that ambivalent sexism is exemplified by two different ideas that people disrespected but liked and disliked but respected (Fiske, Xu, Cuddy & Glick, 1999). This research is focused on how individuating information affects peoples’ responses to women and men when given the same information about them. Individuating information can be thought of as information people use when they are deciding what group someone is grouped into, based on things like job, hobbies, personality etc. This information is perceived differently between males and females because certain characteristics are associated with men and others with women (e.g. men as breadwinners and are strong verses women as homemakers and are caring). This is where the stereotypes come into play. This study is focused on sexism, and what levels (benevolent, ambivalent, hostile) people fall into based on their attitudes towards women, especially in relation to job hiring type situations. Previous research (Eagly, Kulesa, Chen & Chaiken, 2001) suggests that attitudes affect information processing, but they do so by processes that differ depending on whether information agrees or disagrees with recipients’ attitudes. This current study involved the participants rating how the professors would do in certain positions in the University based on their job application. First, in a way that would affect the participant (e.g. would I want to work with this person or would I want this person to be my teacher?) or in more abstract way that wouldn’t affect each individual directly (e.g. likelihood of being an excellent teacher or likelihood of assuming a leadership position) and how those choices are affected by the sex the applicant. I hypothesize that gender and benevolent sexism will be strongly predictive of levels of hostile and ambivalent sexism. I hypothesize that gender, percent of women leaders, suggested salary, success in being a good teacher, success in writing top notch journals and reaction time for negative evaluations will predict positively to hostile and ambivalent sexism. Table 1: Summary statistics for criterion and predictor variables The analyses that were done in this study centered around two criterion variables, ambivalent sexism and hostile sexism. These two scales were used in analysis with 7 predictors: gender, percent of women leaders, benevolent sexism, suggested salary, success in being an excellent teacher, success in writing top notch journals, and RT negative evaluations. In Table 1 it lists the means, std and N for all of the predictors. So the first criterion was ambivalent sexism it had a R²= .779, F (7, 78) = 19.71, p<.01. Also the p-value, b and ß weights are all laid out in Table 2. This model has a significant regression weight and has a p-value of .000. The second was hostile sexism it has a R² =.440, F(7,78), = 2.67, p<.05. Also the p-value, b and ß weights are all laid out in Table 2. This model had a significant regression weight and a p-value of .016. Correlations were done with all of the predictors in which all were correlated with ambivalent and hostile sexism they are listed in Table 2 with the r, b and ß weights for all of the predictors. For the simple correlations: success in pub in top notch journals was negatively correlated with ambivalent and not correlated with hostile sexism. Suggested salary was not correlated to hostile or ambivalent sexism. Gender was positively correlated for both hostile and ambivalent sexism. Success in being an excellent teacher was negatively correlated to ambivalent sexism but not correlated for hostile sexism. Percent of women leaders was not correlated with ambivalent and hostile sexism. Reaction time for negative evaluations wasn’t correlated with hostile and ambivalent sexism. Benevolent sexism was positively correlated with hostile and ambivalent sexism and was the biggest contributing predictor in the whole model. For the whole model criteria compared to each other there was a Z =15.60 showing that the models are different, with a correlation of .859 and p<.01. The full model results found a variety of different findings. The variable gender of the applicant was negatively correlated with both ambivalent and hostile sexism. Benevolent sexism had a positive correlation and the biggest correlation of all the predictors. While percent of women leaders, success in being an excellent teacher suggested salary, success in writing top notch journals, and Reaction time for negative evaluations all had no relationship with ambivalent or hostile sexism. Variables Mean Std N Gender 1.68 .47 257 Percent of woman leaders 39.28 10.98 257 Benevolent sexism 4.03 .82 257 Suggested salary 44565.66 8684.98 257 Success in being an excellent teacher 4.34 1.89 257 Success in pub in top 5.34 1.21 257 notch journals RT Negative evaluations 19404.52 5514.51 86 Ambivalent sexism 3.91 .75 257 Table 2 Correlations and multiple regression weights from models of Ambivalent and Hostile Sexism Ambivalent Sexism Hostile Sexism Variable r b ß p r b ß p Gender -.263** -.240 -.153 .048 -.277** -.481 -.228 .048 Percent of women .016- .001 -.017 .811 .005 -.002 -.026 .941 Leaders Benevolent .775** .704 .750*** .000 . 341** .408 .319*** .003 Sexism Suggested Salary .054 -.0000009 -.010 .895 .000 -.0000018 -.015 .895 Success at being an .127* -.001 -.002 .983 .075 -.002 -.002 .983 excellent teacher Success in pub in top -.126* -.018 -.030 .682 -.120 -.036 -.044 .682 notch journals RT Negative Evaluation .101 .000002 .016 .823 .070 .000004 .024 .823 Method Participants The population used for this study was students of the University of Nebraska-Lincoln. They were recruited by means of extra credit mostly for Psychology classes, and were asked to do a job hiring task. The task involved looking at job applications for supposed professors at the University (these applications were fabricated and formed in terms of negative, positive or neutral kinds) and rate them by answering a series of questions. The mean and std for ethnicity was (M= 3.05, SD=.53) and for gender (M= 1.68, SD= .47). Materials The job applications were made-up for the participants that were either male or female and either containing negative, positive, or neutral individuating information in the applications. These applications were put together by the researcher and pre-tested for accuracy pertaining to negative, positive or neutral characteristics of the applicant. Procedure The purpose was to decide what people’s levels of sexism are based on what kinds of information they are given and how they activate those stereotypes. As the participants began the study and they were told about the study and that it involved looking at job applications for potential University professors because the University was hiring in the Psychology department. The application task involved looking at the job applications: either a male or a female and either an application with negative, positive, or neutral information. The participants were then asked to rate the person, based on a variety of questions that had to do with the information they received (e.g. what do you think the applicant should be paid? Or how successful would the applicant be at being a good teacher) and more personally directed questions (e.g. How likely would you want them to be your advisor? Or what percent of women leaders have you had?). They were also asked to fill out basic demographic information, major etc. The participants were then thoroughly debriefed about the proceedings, allowed to ask questions and given credit. Results The analyses that were done in this study centered around two criterion variables, ambivalent sexism and hostile sexism. These two scales were used in analysis with 7 predictors: gender, percent of women leaders, benevolent sexism, suggested salary, success in being an excellent teacher, success in writing top notch journals, and RT negative evaluations. In Table 1 it lists the means, std and N for all of the predictors. So the first criterion was ambivalent sexism it had a R²= .779, F (7, 78) = 19.71, p<.01. Also the p-value, b and ß weights are all laid out in Table 2. This model has a significant regression weight and has a p-value of .000. The second was hostile sexism it has a R² =.440, F(7,78), = 2.67, p<.05. Also the p-value, b and ß weights are all laid out in Table 2. This model had a significant regression weight and a p-value of .016. Correlations were done with all of the predictors in which all were correlated with ambivalent and hostile sexism they are listed in Table 2 with the r, b and ß weights for all of the predictors. For the simple correlations: success in pub in top notch journals was negatively correlated with ambivalent and not correlated with hostile sexism. Suggested salary was not correlated to hostile or ambivalent sexism. Gender was positively correlated for both hostile and ambivalent sexism. Success in being an excellent teacher was negatively correlated to ambivalent sexism but not correlated for hostile sexism. Percent of women leaders was not correlated with ambivalent and hostile sexism. Reaction time for negative evaluations wasn’t correlated with hostile and ambivalent sexism. Benevolent sexism was positively correlated with hostile and ambivalent sexism and was the biggest contributing predictor in the whole model. For the whole model criteria compared to each other there was a Z =15.60 showing that the models are different, with a correlation of .859 and p<.01. The full model results found a variety of different findings. The variable gender of the applicant was negatively correlated with both ambivalent and hostile sexism. Benevolent sexism had a positive correlation and the biggest correlation of all the predictors. While percent of women leaders, success in being an excellent teacher suggested salary, success in writing top notch journals, and Reaction time for negative evaluations all had no relationship with ambivalent or hostile sexism. Discussion I hypothesized that gender, percent of women leaders and benevolent sexism will be strongly predictive of levels of hostile and ambivalent sexism. It turns out that gender of the applicant and benevolent sexism were both very predictive of activating both ambivalent and hostile sexism, while percent of women leaders was not a big predictor. These are the main contributing variables that will be focused on analysis of the results. These variables can be understood in a less abstract manner shown in previous research (Carli & Eagly, 1999) that has found that people in general are more influential when considered to be more competent. The study also found that men are considered more competent than women; so no matter how competent the women seemed she would still has a hard time being considered as competent as men. In the ambivalent sexism regression percent of women leaders, success in being a good teacher and success in publishing top notch journals were small negative predictors in the beginning but were not significant predictors in the full model. This could be because they are significant but other variables are significant in the same way, and that lower scores on the ambivalence test mean higher ratings on the questions. But no matter what people rate on sexism tests there are still huge overbearing sexism of women as previous research by Carli and Eagly (1999) revealed that men preferred hiring a man or not hiring anyone at all, to hiring a woman whose performance was superior to the man. So decisions sometimes are based just on gender rather than performance, because they are activating a stereotype. These results were interesting because it supports the idea that hostile sexism and ambivalent encompass similar elements but hostile is less positive and immediately activates a stereotype. The limitations of this study do not allow for us to really know why the participants rated the applications how they did or if gender was the only thing that influenced the results. While they did rate the applicants and answered other questions we cannot be sure that the participants answered the questions the same way the questions are being interpreted. This is because like any laboratory study people are being put into an unnatural situation, where they may not react as they would natural. Future research should go a little more in-depth on the relationship between how someone rates males and females based on if the question applies to them directly or not. As was talked about above the difference of responses between would you want this person to be your advisor (personal) and success in writing top notch journals (indirect) and whether that has an effect on what sex people choose. Previous research (Carli & Eagly, 1999) says that when people have nothing to gain from a self-promoting woman they are less likely to hire her than if the participant has something to gain from her. There are many outlets to explore, what characteristic of a women makes that so? There could be many characteristics besides the self-promoting aspect that affect hiring. Maybe expanding it to a wider span, covering a broader range of situations besides hiring. Also something that is interesting would be seeing if men and women equally do this and get down to the specific reasons that women are viewed this way.