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Uncertainty around age at death, or lifetime uncertainty, is a key public health indicator and a marker of inequality in survival. How does the extent of violence affect lifetime uncertainty? We address this question by quantifying the impact of violence on dispersion in the ages at death, the metric most used to measure lifetime uncertainty. Using mortality data from the Global Burden of Disease Study and the Internal Peace Index between 2008 and 2017, we find that the most violent countries are also those with the highest lifetime uncertainty. In the Middle East, conflict-related deaths are the largest contributor to lifetime uncertainty. In Latin America, a similar pattern is attributable to homicides. The effects are larger in magnitude for men, but the consequences remain considerable for women. Our study points to a double burden of violence on longevity: Not only does violence shorten individual lives, but it also makes the length of life less predictable.

Online professional social networking platforms provide opportunities to expand networks strategically for job opportunities and career advancement. A large body of research shows that women's offline networks are less advantageous than men's. How online platforms such as LinkedIn may reflect or reproduce gendered networking behaviours, or how online social connectivity may affect outcomes differentially by gender is not well understood. This paper analyses aggregate, anonymised data from almost 10 million LinkedIn users in the UK and US information technology (IT) sector collected from the site's advertising platform to explore how being connected to Big Tech companies ('social connectivity') varies by gender, and how gender, age, seniority and social connectivity shape the propensity to report job promotions or relocations. Consistent with previous studies, we find there are fewer women compared to men on LinkedIn in IT. Furthermore, female users are less likely to be connected to Big Tech companies than men. However, when we further analyse recent promotion or relocation reports, we find women are more likely than men to have reported a recent promotion at work, suggesting high-achieving women may be self-selecting onto LinkedIn. Even among this positively selected group, though, we find men are more likely to report a recent relocation. Social connectivity emerges as a significant predictor of promotion and relocation reports, with an interaction effect between gender and social connectivity indicating the payoffs to social connectivity for promotion and relocation reports are larger for women. This suggests that online networking has the potential for larger impacts for women, who experience greater disadvantage in traditional networking contexts, and calls for further research to understand differential impacts of online networking for socially disadvantaged groups., Comment: Accepted and forthcoming at the International AAAI Conference on Web and Social Media (ICWSM) 2024

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Background: Marriage is a central institution for social reproduction in East Asia. Until the 1970s and 1980s, marriage across much of East Asia was early and universal. In recent decades, though, this pattern has begun shifting to one of later and less marriage. Objective: We explore the long-term implications for universal marriage patterns of future demographic change in marriage markets in the context of prevailing marriage norms by projecting trends in late singlehood (ages 45 to 49) in four East Asian societies (China, South Korea, Taiwan, and Japan). Methods: We estimate forces of attraction to characterize marriage matching norms by age and education across these different societies by drawing on large-scale population data. Next, we develop counterfactual scenarios in which we apply contemporary norms to future population structures in these societies, as well as scenarios based on more gender-symmetrical matching norms to examine how populations who have never been married by ages 45 to 49 would evolve. Results: Our projections indicate that in the coming decades there will be a substantial increase in late singlehood across all these societies relative to their 2010 levels. These increases in singlehood are driven by forthcoming demographic changes in the marriage market that intensify the effects of prevailing matching norms. These increases are notable in Taiwan and South Korea, where recent data indicate generalized weak propensities to marry in current norms. While a shift toward greater gender symmetry in matching norms would reverse gender gaps between men and women in nonmarriage, it would have little impact on the overall projected proportions of singles by ages 45 to 49. Conclusions: If prevailing norms in each of these contexts continue, the universality of marriage will be substantially eroded in the coming decades, even if norms become more gender symmetrical. The extent to which nonmarital cohabitation and childbearing emerge in the future wi

Marriage is a central institution for social reproduction in East Asia. Until the 1970s and 1980s, marriage across much of East Asia was early and universal. In recent decades, though, this pattern has begun shifting to one of later and less marriage. We explore the long-term implications for universal marriage patterns of future demographic change in marriage markets in the context of prevailing marriage norms by projecting trends in late singlehood (ages 45 to 49) in four East Asian societies (China, South Korea, Taiwan, and Japan).We estimate forces of attraction to characterize marriage matching norms by age and education across these different societies by drawing on large-scale population data. Next, we develop counterfactual scenarios in which we apply contemporary norms to future population structures in these societies, as well as scenarios based on more gender-symmetrical matching norms to examine how populations who have never been married by ages 45 to 49 would evolve.Our projections indicate that in the coming decades there will be a substantial increase in late singlehood across all these societies relative to their 2010 levels. These increases in singlehood are driven by forthcoming demographic changes in the marriage market that intensify the effects of prevailing matching norms. These increases are notable in Taiwan and South Korea, where recent data indicate generalized weak propensities to marry in current norms. While a shift toward greater gender symmetry in matching norms would reverse gender gaps between men and women in nonmarriage, it would have little impact on the overall projected proportions of singles by ages 45 to 49.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

The reversal of the gender gap in higher education has been a major social transformation: women now outnumber men in higher education in nearly all OECD countries. Patterns of assortative mating have also changed as highly educated women increasingly form relationships with men who have less education (hypogamous unions). In this article, we draw on rich register data from Sweden to ask whether the emergence of hypogamous unions signals the emergence of a new female status dominance in unions. We also consider how the status distribution in these unions compares to homogamous (both highly educated) or hypergamous (he highly educated) unions. We use Swedish register data and study couples who have their first child together. We refer to a multi-dimensional view of status and use indicators of social class background, income, and occupational prestige. We find that in hypogamous unions, women tend to have a higher social class background and occupational prestige, but lower income than their partners. The income gap between partners is not simply a consequence of the gender wage gap, but driven by selection into different union types. Men and women who form hypogamous unions are negatively selected in terms of their income.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Survey data sets are often wider than they are long. This high ratio of variables to observations raises concerns about overfitting during prediction, making informed variable selection important. Recent applications in computer science have sought to incorporate human knowledge into machine-learning methods to address these problems. The authors implement such a “human-in-the-loop” approach in the Fragile Families Challenge. The authors use surveys to elicit knowledge from experts and laypeople about the importance of different variables to different outcomes. This strategy offers the option to subset the data before prediction or to incorporate human knowledge as scores in prediction models, or both together. The authors find that human intervention is not obviously helpful. Human-informed subsetting reduces predictive performance, and considered alone, approaches incorporating scores perform marginally worse than approaches that do not. However, incorporating human knowledge may still improve predictive performance, and future research should consider new ways of doing so.

Survey data sets are often wider than they are long. This high ratio of variables to observations raises concerns about overfitting during prediction, making informed variable selection important. Recent applications in computer science have sought to incorporate human knowledge into machine-learning methods to address these problems. The authors implement such a “human-in-the-loop” approach in the Fragile Families Challenge. The authors use surveys to elicit knowledge from experts and laypeople about the importance of different variables to different outcomes. This strategy offers the option to subset the data before prediction or to incorporate human knowledge as scores in prediction models, or both together. The authors find that human intervention is not obviously helpful. Human-informed subsetting reduces predictive performance, and considered alone, approaches incorporating scores perform marginally worse than approaches that do not. However, incorporating human knowledge may still improve predictive performance, and future research should consider new ways of doing so.

Over the last decades, women have outperformed men in higher education. Following this trend, women have also increasingly “partnered down” in terms of education. In this paper, we ask whether this trend for women’s educational hypogamy (“partnering down”) corresponds to other forms of status hypogamy, and whether the increasing prevalence of educationally hypogamous unions has accounted for changes in the status of women relative to their male partners across cohorts. We use Swedish register data and analyze childbearing unions of post-secondary educated men and women born in 1950-2, 1960-2, 1970-2, and 1980-2. We measure relative status according to social class background, income, and occupational prestige. Female hypogamous unions are only somewhat more female status-dominant than other unions. We also find that the status of women relative to their male partners over time has been generally stable in terms of the different status indicators measured, despite increasing female hypogamy.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Uncertainty around age at death, or lifetime uncertainty, is a key public health indicator and a marker of inequality in survival. How does the extent of violence affect lifetime uncertainty? We address this question by quantifying the impact of violence on dispersion in the ages at death, the metric most used to measure lifetime uncertainty. Using mortality data from the Global Burden of Disease Study and the Internal Peace Index between 2008 and 2017, we find that the most violent countries are also those with the highest lifetime uncertainty. In the Middle East, conflict-related deaths are the largest contributor to lifetime uncertainty. In Latin America, a similar pattern is attributable to homicides. The effects are larger in magnitude for men, but the consequences remain considerable for women. Our study points to a double burden of violence on longevity: Not only does violence shorten individual lives, but it also makes the length of life less predictable.