Pre-Occupation: A Meta-Analysis and Meta-Regression of Gender Differences in Adolescent Vocational Interests

Vocational interests have important implications for a range of life outcomes, such as satisfaction with career choice. Extending research on gender differences in vocational interests with adult samples, we sought to evaluate whether a similar pattern emerged during adolescence in a meta-analysis and explored moderators via meta-regression. Examining 41 studies using 3-level meta-analysis, gender differences in vocational interests are substantially accounted for using Holland’s RIASEC framework. Male adolescents have higher interests in Realistic and Investigative careers and female adolescents have higher interests in Social and Artistic careers. The differences were not moderated by year, national gender inequality ratings, or scale type. The study highlights that there are patterns in gender differences in the vocational interests of adolescents, that these differences reflect those found with adult samples, and that the differences have been stable over the past 80 years.

Using social media advertisement data to monitor the gender gap in STEM: opportunities and challenges

Boosting the number of women and girls entering careers involving STEM (Science, Technology, Engineering and Maths) is crucial to achieving gender equality, one of the UN Sustainable Development Goals. Girls and women tend to gravitate away from STEM fields at multiple stages from childhood through mid-career. The leaky pipeline is a metaphor often used to describe the loss of women in STEM and arguably other fields before reaching senior roles. Do interests expressed on social media mirror the leaky pipeline phenomenon? In this article, we collected advertisement data (reach estimates) from Facebook and Instagram disaggregated by US metros, age, gender, and interests related to STEM. We computed the Gender Gap Index (GGI) for each US metro and age group. We found that on Instagram, the GGIs for interest in Science decrease as users' age increases, suggesting that relatively there is evidence that that women, compared to men, are losing interest in STEM at older ages. In particular, we find that on Instagram, there are plausible relative trends but implausible absolute levels. Nevertheless, is this enough to conclude that online data available from Instagram mirror the leaky pipeline phenomenon? To scrutinize this, we compared the GGIs for an interest in Science with the GGIs for placebo interests unrelated to STEM. We found that the GGIs for placebo interests follow similar age patterns as the GGIs for the interest in Science across US metros. Second, we attempted to control for the time spent on the platform by computing a usage intensity gender ratio based on the difference between daily and monthly active users. This analysis showed that the usage intensity gender ratio is higher among teenagers (13-17 years) than other older age groups, suggesting that teenage girls are more engaged on the platform that teenage boys. We hypothesize that usage intensity differences, rather than inherent interest changes, might create the illusion of a leaky pipeline. Despite the previously demonstrated value and huge potential of social media advertisement data to study social phenomena, we conclude that there is little evidence that this novel data source can measure the decline in interest in STEM for young women in the USA.

Math anxiety affects females' vocational interests

Vocational interest in science, technology, engineering, and math (STEM) fields in middle school can predict life outcomes, including enrollment in STEM courses and pursuing STEM careers. Numerical performance, as well as emotional factors such as math anxiety (MA), may influence vocational interests. The constructs of both vocational interests and MA are sensitive to gender differences. Accordingly, this study explored whether the relations among MA, numerical performance, and math vocational interests among middle-school students vary by gender. A sample of 127 ninth-grade students (68 females) performed a computation task and completed MA and trait anxiety (TA) questionnaires. A math vocational interest questionnaire was composed and assessed with an additional sample of 89 ninth-grade students. For females, MA, but not TA or numerical performance, predicted math vocational interest. Those with low MA levels tended to be interested in careers with higher math proficiency such as STEM careers. For males, high numerical performance and low TA, but not MA, related to interest in careers with high math proficiency. Bayes factors indicated that the data strongly supported the theory. The findings support the assumption that high MA levels affect the career plans of female students, whereas low numerical performance can account for both MA levels and future career plans of male students. It is essential to investigate how career aspirations are shaped in young students to promote the choice of STEM careers, especially among underrepresented populations such as females.

Negligible effects of birth order on selection into scientific and artistic careers, creativity, and status attainment

We tested birth order effects on selection into different careers (scientific, artistic, and creative) and status attainment (educational attainment, occupational prestige, and income) using a large sample ( n = 3763), a longitudinal design, and relevant controls. Additionally, we tested mediation of birth order effects on career outcomes via personality traits, intelligence, and educational attainment. We found negligible birth order effects ranging from 0.02 to 0.12 on a correlational metric, where firstborns (vs. laterborns) selected into more creative careers and attained higher prestige and education. Conditional on the theoretically based mediation models tested, results showed that intelligence and educational attainment (but not personality traits) accounted for a statistically significant portion of the variance in the links between birth order and career outcomes. No direct effects of birth order on career outcomes remained when accounting for indirect effects through educational attainment. These findings bring modest support to the confluence model, no support to the niche-finding model, and suggest that one possible route via which birth order might impact career outcomes (if at all) could be via educational attainment.