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Automatically collected behavioral data on the location of users of mobile phones offer an unprecedented opportunity to measure mobilization in mass protests, while simultaneously expanding the range of researchable questions. Location data not only improve estimation of the number and composition of participants in large demonstrations. Thanks to high spatial and temporal resolution they also reveal when, where, and with whom different sociopolitical sectors join a protest campaign. This article compares the features and advantages of this type of data with other methods of measuring who participates in street protests. The steps in preparing a usable data set are explained with reference to a six-week campaign of mass mobilization in Israel in 2011. Findings based on the Israeli data set illustrate a wide range of potential applications, pertaining to both the determinants and consequences of protest participation. Limitations of mobile location data and the privacy issues it raises are also discussed.

The expansion of women's educational attainment may seem to be a promising path toward achieving economic equality between men and women, given the consistent rise in the economic value of higher education. Using yearly data from 1980 to 2017, we provide an updated and comprehensive examination of the gender gap in education premiums, showing that it is not as promising as it could and should be. Women receive lower rewards to their higher education across the entire wage distribution, and this gender gap increases at the very top education premiums—the top quarter and, even more so, the top decile. Moreover, insufficient theoretical and methodological attention to this top premium effect has left gender inequality concealed in the extensive empirical studies on the topic. Specifically, when we artificially censor the top at the 80th wage percentile, the gender gaps in education premium reverse. Lastly, the growth in earnings inequality in the United States, which is greatly affected by the expansion of top earnings, is associated with the growing gender gap in education premiums over time. We discuss the meaning and implications of this structural disadvantage at a time when women's educational advantage keeps growing and higher education remains the most important factor for economic attainment.

The steep rise of top wages is acknowledged as one of the main drivers of the rise in earnings inequality between workers in most postindustrial labor markets. Yet its relation to gender stratification, in particular to the stagnation in the gender pay gap, has received very little scholarly attention. Using data from the U.S. Current Population Survey, conducted between 1980 and 2017, we provide evidence of the enormous weight that the dynamic at the top of the earnings distribution exerts on the gender pay gap. We also show how this dynamic inhibits the consequences of the countervailing process of gender vertical desegregation. Although developments in gender inequality and in the rise of top wages have drawn extensive scholarly attention and have even penetrated into the public discourse in recent years, the two dimensions of inequality are often perceived as unrelated to one another. Our findings, then, highlight the connection between different forms of inequality-class inequality and gender inequality-a relation that demands much more attention in the new economy.

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