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Institute
Can we rely on computational methods to accurately analyze complex texts? To answer this question, we compared different dictionary and scaling methods used in predicting the sentiment of German literature reviews to the "gold standard " of human-coded sentiments. Literature reviews constitute a challenging text corpus for computational analysis as they not only contain different text levels-for example, a summary of the work and the reviewer's appraisal-but are also characterized by subtle and ambiguous language elements. To take the nuanced sentiments of literature reviews into account, we worked with a metric rather than a dichotomous scale for sentiment analysis. The results of our analyses show that the predicted sentiments of prefabricated dictionaries, which are computationally efficient and require minimal adaption, have a low to medium correlation with the human-coded sentiments (r between 0.32 and 0.39). The accuracy of self-created dictionaries using word embeddings (both pre-trained and self-trained) was considerably lower (r between 0.10 and 0.28). Given the high coding intensity and contingency on seed selection as well as the degree of data pre-processing of word embeddings that we found with our data, we would not recommend them for complex texts without further adaptation. While fully automated approaches appear not to work in accurately predicting text sentiments with complex texts such as ours, we found relatively high correlations with a semiautomated approach (r of around 0.6)-which, however, requires intensive human coding efforts for the training dataset. In addition to illustrating the benefits and limits of computational approaches in analyzing complex text corpora and the potential of metric rather than binary scales of text sentiment, we also provide a practical guide for researchers to select an appropriate method and degree of pre-processing when working with complex texts.
Who suffered most?
(2022)
Objective:
This study examines gender and socioeconomic inequalities in parental psychological wellbeing (parenting stress and psychological distress) during the COVID-19 pandemic in Germany.
Background:
The dramatic shift of childcare and schooling responsibility from formal institutions to private households during the pandemic has put families under enormous stress and raised concerns about caregivers' health and wellbeing. Despite the overwhelming media attention to families’ wellbeing, to date limited research has examined parenting stress and parental psychological distress during the COVID-19 pandemic, particularly in Germany.
Method:
We analyzed four waves of panel data (N= 1,771) from an opt-in online survey, which was conducted between March 2020 and April 2021. Multivariable OLS regressions were used to estimate variations in the pandemic's effects on parenting stress and psychological distress by various demographic and socioeconomic characteristics.
Results:
Overall, levels of parenting stress and psychological distress increased during the pandemic. During the first and third wave of the COVID-19 pandemic, mothers, parents with children younger than 11 years, parents with two or more children, parents working from home as well as parents with financial insecurity experienced higher parenting stress than other sociodemographic groups. Moreover, women, respondents with lower incomes, single parents, and parents with younger children experienced higher levels of psychological distress than other groups.
Conclusion:
Gender and socioeconomic inequalities in parents' psychological wellbeing increased among the study participants during the pandemic.
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.
This study examines how public policies affect parents' preferences for a more egalitarian division of paid and unpaid work. Based on the assumption that individuals develop their preferences within a specific policy context, we examine how changes in three policies affect mothers' and fathers' work-family preferences: the availability of high-quality, affordable childcare; the right to return to a full-time job after having reduced hours to part-time and an increase in the number of 'partner months' in parental leave schemes. Analysing a unique probability sample of parents with young children in Germany from 2015 (N = 1756), we find that fathers would want to work slightly fewer hours if they had the right to return to a full-time position after working part-time, and mothers would want to work slightly more hours if childcare opportunities were improved. Full-time working parents, moreover, are found to prefer fewer hours independent of the policy setting, while non-employed parents would like to work at least some hours. Last but not least, our analyses show that increasing the number of partner months in the parental leave scheme considerably increases fathers' preferences for longer and mothers' preferences for shorter leave. Increasing the number of partner months in parental schemes hence has the greatest potential to increase gender equality.
Cross-national variation in the relationship between welfare generosity and single mother employment
(2022)
Reform of the U.S. welfare system in 1996 spurred claims that cuts to welfare programs effectively incentivized single mothers to find employment. It is difficult to assess the veracity of those claims, however, absent evidence of how the relationship between welfare benefits and single mother employment generalizes across countries. This study combines data from the European Union Labour Force Survey and the U.S. Current Population Survey (1992-2015) into one of the largest samples of single mothers ever, testing the relationships between welfare generosity and single mothers’ employment and work hours. We find no consistent evidence of a negative relationship between welfare generosity and single mother employment outcomes. Rather, we find tremendous cross-national heterogeneity, which does not clearly correspond to well-known institutional variations. Our findings demonstrate the limitations of single country studies and the pervasive, salient interactions between institutional contexts and social policies.