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Pandemic depression
(2022)
We investigate the effect of the COVID-19 pandemic on self-employed people’s mental health. Using representative longitudinal survey data from Germany, we reveal differential effects by gender: whereas self-employed women experienced a substantial deterioration in their mental health, self-employed men displayed no significant changes up to early 2021. Financial losses are important in explaining these differences. In addition, we find larger mental health responses among self-employed women who were directly affected by government-imposed restrictions and bore an increased childcare burden due to school and daycare closures. We also find that self-employed individuals who are more resilient coped better with the crisis.
Introduction
(2022)
Several global governance initiatives launched in recent years have explicitly sought to integrate concern for gender equality and gendered harms into efforts to counter terrorism and violent extremism (CT/CVE). As a result, commitments to gender-sensitivity and gender equality in international and regional CT/CVE initiatives, in national action plans, and at the level of civil society programming, have become a common aspect of the multilevel governance of terrorism and violent extremism. In light of these developments, aspects of our own research have turned in the past years to explore how concerns about gender are being incorporated in the governance of (counter-)terrorism and violent extremism, and how this development has affected (gendered) practices and power relations in counterterrorism policymaking and implementation. We were inspired by the growing literature on gender and CT/CVE, and critical scholarship on terrorism and political violence, to bring together a collection of new research addressing these questions.
We collect a network dataset of tenured economics faculty in Austria, Germany and Switzerland. We rank the 100 institutions included with a minimum violation ranking. This ranking is positively and significantly correlated with the Times Higher Education ranking of economics institutions. According to the network ranking, individuals on average go down about 23 ranks from their doctoral institution to their employing institution. While the share of females in our dataset is only 15%, we do not observe a significant gender hiring gap (a difference in rank changes between male and female faculty). We conduct a robustness check with the Handelsblatt and the Times Higher Education ranking. According to these rankings, individuals on average go down only about two ranks. We do not observe a significant gender hiring gap using these two rankings (although the dataset underlying this analysis is small and these estimates are likely to be noisy). Finally, we discuss the limitations of the network ranking in our context.
Objective: This article analyzed gender differences in professional advancement following the outbreak of the Covid-19 pandemic based on data from open-source software developers in 37 countries. Background: Men and women may have been affected differently from the social distancing measures implemented to contain the Covid-19 pandemic. Given that men and women tend to work in different jobs and that they have been unequally involved in childcare duties, school and workplace closings may have impacted men's and women's professional lives unequally. Method: We analyzed original data from the world's largest social coding community, GitHub. We first estimated a Holt-Winters forecast model to compare the predicted and the observed average weekly productivity of a random sample of male and female developers (N=177,480) during the first lockdown period in 2020. To explain the crosscountry variation in the gendered effects of the Covid-19 pandemic on software developers' productivity, we estimated two-way fixed effects models with different lockdown measures as predictors - school and workplace closures, in particular. Results: In most countries, both male and female developers were, on average, more productive than predicted, and productivity increased for both genders with increasing lockdown stringency. When examining the effects of the most relevant types of lockdown measures separately, we found that stay-at-home restrictions increased both men's and women's productivity and that workplace closures also increased the number of weekly contributions on average - but for women, only when schools were open. Conclusion: Having found gender differences in the effect of workplace closures contingent on school and daycare closures within a population that is relatively young and unlikely to have children (software developers), we conclude that the Covid-19 pandemic may indeed have contributed to increased gender inequalities in professional advancement.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.