Gender imbalances in work environments have been a long-standing concern. Identifying the existence of such imbalances is key to designing policies to help overcome them. In this work, we study gender trends in employment across various dimensions in the United States. This is done by analyzing anonymous, aggregate statistics that were extracted from LinkedIn's advertising platform. The data contain the number of male and female LinkedIn users with respect to (i) location, (ii) age, (iii) industry and (iv) certain skills. We studied which of these categories correlate the most with high relative male or female presence on LinkedIn. In addition to examining the summary statistics of the LinkedIn data, we model the gender balance as a function of the different employee features using linear regression. Our results suggest that the gender gap varies across all feature types, but the differences are most profound among industries and skills. A high correlation between gender ratios of people in our LinkedIn data set and data provided by the US Bureau of Labor Statistics serves as external validation for our results.
Our science, technology, engineering and math (STEM) workforce is crucial to America’s innovative capacity and global competitiveness. Yet women are vastly underrepresented in STEM jobs and among STEM degree holders despite making up nearly half of the U.S. workforce and half of the college-educated workforce. That leaves an untapped opportunity to expand STEM employment in the United States, even as there is wide agreement that the nation must do more to improve its competitiveness.Although women fill close to half of all jobs in the U.S. economy, they hold less than 25 percent of STEM jobs. This has been the case throughout the past decade, even as college-educated women have increased their share of the overall workforce.Women with STEM jobs earned 33 percent more than comparable women in non-STEM jobs – considerably higher than the STEM premium for men. As a result, the gender wage gap is smaller in STEM jobs than in non-STEM jobs.Women hold a disproportionately low share of STEM undergraduate degrees, particularly in engineering.Women with a STEM degree are less likely than their male counterparts to work in a STEM occupation; they are more likely to work in education or healthcare.There are many possible factors contributing to the discrepancy of women and men in STEM jobs, including: a lack of female role models, gender stereotyping, and less family-friendly flexibility in the STEM fields. Regardless of the causes, the findings of this report provide evidence of a need to encourage and support women in STEM. Background Understanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data. Purpose This article explores the relationship between online social environment via web-based social networks and population obesity prevalence. Methods We performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook. Results Higher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0 (95 Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and or overweight people across USA metros and 7.2 (95 CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and or overweight people of 3.9 (95 CI: 3.7 to 4.0) (USA) and 27.5 (95 CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set. Conclusions Activity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions. This paper studies the gender compensation gap among high-level executives in US corpora- tions. We use the ExecuComp data set that contains information on total compensation for the top five highest paid executives of a large group of US firms over the period 1992-1997. About 2.5 of the executives in the sample are women. These women earn about 45 less than their male counterparts. As much as 75 of this gap can be accounted for by the fact that women manage smaller companies and are less likely to be CEO; Chair, or President of their company. The unexplained gender gap can be reduced to less than 5 when one further accounts for the fact that female executives are younger and have less seniority than male executives. Over the period under study, women have nearly tripled their participation in the top executive ranks and have also strongly improved their relative compensation, mostly by gaining representation into the larger corporations. While the absence of a significant conditional gender gap implies that women and men who hold similar jobs in firms of similar size receive fairly equal treatment in terms of compensation, it does not rule out the possibility of discrimination in terms of gender segregation or promotion. 