Interestingly enough, a second study has now replicated the these findings for teams that worked together online communicating purely by typing messages into a browser . "Emotion-reading mattered just as much for the online teams whose members could not see one another as for the teams that worked face to face. What makes teams smart must be not just the ability to read facial expressions, but a more general ability, known as "Theory of Mind," to consider and keep track of what other people feel, know and believe."
The average score for this test is in the range of 22 to 30 correct responses. If you scored above 30, you may be quite good at understanding someone’s mental state based on facial cues. If you scored below 22, you may find it difficult to understand a person’s mental state based on their appearance.
In a recent study, researchers from University of California, Davis and Eindhoven University of Technology, The Netherlands have analyzed the effects of gender and tenure diversity on productivity and turnover for more than 23,000 open-source projects on GitHub. Using regression modeling, they showed that after controlling for team size and other confounds (such as a project's age, development model, or amount of social activity), both gender and tenure diversity are positive and significant predictors of productivity, together explaining a small but significant fraction of the data variability. On an economic and societal scale, these findings suggest that added investments in educational and professional training efforts and outreach for female programmers will likely result in added overall value.
The paper describing the results (preprint PDF here) will be presented at the prestigious ACM CHI Conference on Human Factors in Computing Systems, in Seoul, South Korea, in April 2015.