The persistence of gender stereotypes in the USA as well as the rest of the world is one of the most burning issues. These stereotypes often pose various barriers to people’s entry into this or that sphere. It is necessary to note that the research of stereotypes is often associated with the use of qualitative methods as researchers are often interested in opinions, beliefs and motivations. Croft et al. (2014) used quantitative methods to assess the extent to which the stereotypes are developed within families.
It is possible to note that quantitative research method can unveil many important trends existing in the society. When addressing the issues concerning gender stereotypes in families, it is possible to explore the way parents’ jobs, as well as implicit and explicit beliefs concerning gender roles, correlate with stereotypes in their children. It is possible to estimate the percentage of families where stereotypes are persistent through analyzing questionnaires completed by parents and children. The focus can be made on families where parents have ‘non-typical’ for their gender jobs.
This quantitative research will provide numerical data that will reveal the extent to which parents’ experiences affect their children’s stereotypes. The quantitative research will provide particular evidence that support the existing bulk of knowledge (Howitt & Cramer, 2014). This type of research also helps generalize data obtained and apply to larger populations.
Nonetheless, it also has certain limitations. First, the study mentioned is very time consuming. It is vital to include a significant number of samples to ensure the research’s validity. In its turn, the large number of participants will need significant effort and skills (). Thus, a significant amount of time will be necessary to collect and analyze the data. It is also important to have the necessary skills to apply statistical tools to ensure relevance and validity of the research.
The article in question focuses on gender stereotypes in the academic environment. Moss-Racusin, Dovidio, Brescoll, Graham & Handelsman (2012) explored the degree to which science faculty have a bias against female students. The researchers stress that the bias exists and it is important to introduce certain training to faculty members to increase female participation in science.
The primary dependent variable was hiring for the position of a laboratory manager. Secondary variables were the perceived students’ competence, salary and student’s being appropriate for faculty mentoring. All these variables show the extent of bias (Moss-Racusin et al., 2012). The independent variable was the gender of the students.
The researchers employed a randomized double-blind study. More than 100 science professors evaluated a science student’s application for the position of a science laboratory manager. All the applications were identical apart from the name of an applicant, which was male or female. This is an experimental study as the participants’ behavior in the preconditioned situation was observed.
This design has a particular scientific merit as it unveils the degree of bias in a particular group of people. This research could be implemented in a slightly different way. I would provide several applications to each participant, which would increase the validity of the experiment. The need to compare would make the participants’ reveal their bias in a more effective way. However, it is possible to note that the research under consideration answers the research questions efficiently. Simple evaluation of people’s perception would be associated with more bias as people tend to conceal their true opinions in many cases.
As to experimental studies, ethical issues may arise. How is it possible to inform the participant about their participation in the study and avoid the John Henry effect?
Reference List
Croft, A., Schmader, T., Block, K., & Baron, A.S. (2014). The second shift reflected in the second generation: Do parents’ gender roles at home predict children’s aspirations? Psychological Science, 1-14.
Howitt, D., & Cramer, D. (2007). Introduction to research methods in psychology. New York, NY: Pearson Education Limited.
Moss-Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham, M.J. & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences of the United States of America, 109(41), 16474-16479.
Steiner, P.M., & Cook, D. (2006). Matching and propensity scores. In T.D. Little (Ed.), The Oxford handbook of quantitative methods in psychology: Foundations (pp. 237-260). New York, NY: Oxford University Press.