Gendered behavior as a disadvantage in open source software development

Women are severely marginalized in software development, especially in open source. In this article we argue that disadvantage is more due to gendered behavior than to categorical discrimination: women are at a disadvantage because of what they do, rather than because of who they are. Using data on entire careers of users from GitHub.com, we develop a measure to capture the gendered pattern of behavior: We use a random forest prediction of being female (as opposed to being male) by behavioral choices in the level of activity, specialization in programming languages, and choice of partners. We test differences in success and survival along both categorical gender and the gendered pattern of behavior. We find that 84.5% of women's disadvantage (compared to men) in success and 34.8% of their disadvantage in survival are due to the female pattern of their behavior. Men are also disadvantaged along their interquartile range of the female pattern of their behavior, and users who don't reveal their gender suffer an even more drastic disadvantage in survival probability. Moreover, we do not see evidence for any reduction of these inequalities in time. Our findings are robust to noise in gender recognition, and to taking into account particular programming languages, or decision tree classes of gendered behavior. Our results suggest that fighting categorical gender discrimination will have a limited impact on gender inequalities in open source software development, and that gender hiding is not a viable strategy for women

Inclusion unlocks the creative potential of gender diversity in teams

Diversity in teams can boost creativity, and gender diversity was shown to be a contributor to collective creativity. We show that gender diversity requires inclusion to lead to benefits in creativity by analyzing teams in 4011 video game projects. Recording data on the weighted network from past collaborations, we developed four measures of inclusion, depending on a lack of segregation, strong ties across genders, and the incorporation of women into the core of the team s network. We found that gender diversity without inclusion does not contribute to creativity, while with maximal inclusion one standard deviation change in diversity results in .04 to .09 standard deviation change in creativity, depending on the measure of inclusion. To reap creative benefits of diversity, developer firms need to include 23 percent or more female developers (as opposed to the 15 percent mean female proportion) and include them in the team along all dimensions. Inclusion at low diversity has a negative effect. By analyzing the sequences of diversity and inclusion across games within firms, we found that adding diversity first, and developing inclusion later can lead to higher diversity and inclusion, compared to adding female developers with already existing cross-gender ties to the team

Reconstructing social mixing patterns via weighted contact matrices from online and representative surveys

The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices, usually stratified by age, summarise interaction motifs efficiently, but their collection relies on conventional representative survey techniques, which are expensive and slow to obtain. Here we report a data collection effort involving over 2.3% of the Hungarian population to simultaneously record contact matrices through a longitudinal online and sequence of representative phone surveys. To correct non-representative biases characterising the online data, by using census data and the representative samples we develop a reconstruction method to provide a scalable, cheap, and flexible way to dynamically obtain closer-to-representative contact matrices. Our results demonstrate that although some conventional socio-demographic characters correlate significantly with the change of contact numbers, the strongest predictors can be collected only via surveys techniques and combined with census data for the best reconstruction performance. We demonstrate the potential of combined online-offline data collections to understand the changing behavioural responses determining the future evolution of the outbreak, and to inform epidemic models with crucial data

„A cigány kártya” : a cigányellenesség megnyilvánulási formái a szélsőjobboldali parlamenti felszólalásokban

The present paper aims to investigate the rhetoric of the Hungarian far right about Roma bythe Parliamentary speeches of far right politicians. It unfolds the topics, discourses how the MPsof MIÉP and Jobbik talked about Roma. Within these topics it examines the different representations, images of Roma used by far right politicians during those Parliamentary terms during which they entered the Parliament. The paper identifies when and how the far right has talkedabout Roma and unfolds how the far right rhetoric has contributed to maintaining, reproducing or even strengthening the anti-Roma attitudes in the Hungarian society