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This study investigates trends in gender inequality throughout the world. Using data encompassing a large majority of the world's population, we examine trends in recent decades for key indicators of gender inequality in education, mortality, political representation and economic activity. We find that gender inequality is declining in virtually all major domains, that the decline is occurring across diverse religious and cultural traditions, and that population growth is slowing the decline because populations are growing faster in countries where there is the greatest gender inequality.

This research introduces a new measure of the socioeconomic status (SES) of countries to test assertions regarding a contemporary world-system in which mobility is scarce or altogether absent. Historical, country-level estimates of population size, income per capita, and educational attainment were used to construct a new time-series measure of SES for a constant panel of 74 countries and a larger, partially imputed panel of 149 countries. Correlation and contingency table analysis show that SES position in 2010 was highly dependent on 1880 position, though the degree of observed immobility is sensitive to the number of status categories and number of countries. The long-run trend has been toward greater mobility and a more open global stratification system that coincides with recent declines in between-nation income and education inequality. Although most highand low-SES countries in 1880 were in the same category in 2010, countries in the middle of the 1880 global status hierarchy were exceptionally mobile over the ensuing 130 years. Population dynamics have played a fundamental role in structuring the global status hierarchy. Low population growth among high-SES countries, coupled with high population growth among low-SES countries, has contributed to substantial expansion and diversification of the high status club, which currently includes a large and growing number of non-western countries.

Over the last decade, there has been an ongoing revolution in the exploration, manipulation and synthesis of biological systems, through the development of new technologies that generate, analyse and exploit big data. Users of Plant Genetic Resources (PGR) can potentially leverage these capacities to significantly increase the efficiency and effectiveness of their efforts to conserve, discover and utilise novel qualities in PGR, and help achieve the Sustainable Development Goals (SDGs). This review advances the discussion on these emerging opportunities and discusses how taking advantage of them will require data integration and synthesis across disciplinary, organisational and international boundaries, and the formation of multidisciplinary, international partnerships. We explore some of the institutional and policy challenges that these efforts will face, particularly how these new technologies may influence the structure and role of research for sustainable development, ownership of resources, and access and benefit sharing. We discuss potential responses to political and institutional challenges, ranging from options for enhanced structure and governance of research discovery platforms to internationally brokered benefit-sharing agreements, and identify a set of broad principles that could guide the global community as it seeks or considers solutions.

This research challenges the notion that the second half of the twentieth century was a period of global demographic convergence. To be sure, fertility rates fell substantially during the period, but with considerable unevenness. The declines in total fertility across population-weighted countries were sufficiently disproportionate that intercountry fertility inequality, estimated using standard measures of inequality, did not begin to decline until at least 1995. Regression analysis also shows that only very recently did lagging countries begin to catch up with countries that began the transition to low fertility earlier. Contrary to findings on changing intercountry health inequality, sub-Saharan Africa has had a greater impact on changes in fertility inequality than China. The trend in fertility inequality, where convergence is a relatively new phenomenon, stands in contrast to trends in inequality in other domains, such as income, education, and health.

The ideas contained in this work were developed during two virtual meetings of members of the Agricultural Genome to Phenome Initiative (AG2PI; www.ag2pi.org) community and leadership team in May and June of 2021. Schedule the social, or “soft” sciences and public impact, communications, and outreach discussions for late in the day; the real science topics will have been fully vetted by then so the real scientists can catch that early flight home: leave the soft stuff for the “others.” Should a team member provide allegations of sexual misconduct or harassment, do not take action or inform the proper authorities. [...]they often identify more novel approaches, see greater breakthroughs, and provide a competitive edge over other teams.

This research documents long-run trends in between-country education inequality and proposes a method for doing so that accounts for the ways in which most education variables differ from continuous variables such as income. Historical, national-level estimates of primary schooling enrollment rates and years of completed primary, secondary, and total schooling are used to identify several problems that arise when formal measures of inequality are used to estimate intercountry education convergence, including violation of the welfare, scale invariance, and anonymity principles. An alternate measurement strategy shows that the intercountry trend in the dispersion of education has followed an approximately normal curve over the past 140 years, but with considerable variation across measures of education. These results are in contradiction to previous education inequality studies, which have reported either monotonically rising or falling intercountry inequality.

Vocabulary test score trends from the General Social Survey contradict the widespread conclusion that scores on standardized intelligence tests have systematically increased over the past century. We use a vocabulary test included in 20 nationally representative surveys administered since 1974 to test three hypotheses proposed to account for these trends, including changes in the formal measurement properties of the test, over-time changes in the meaning of education, and intercohort differences in exposure to words on the test. We find no support for the idea that test scores have declined because of changes in the structure of the test. Instead, our results show that education selectivity accounts for some cohort differences among prewar cohorts and that cohort-specific differences in exposure to words on the test account for nearly all variation in vocabulary scores of respondents born after 1945, suggesting different causal processes have influenced cohort verbal ability during distinct historical eras.

To better understand the long‐term effects of rapid boom growth, we reexamine four subjective indicators of community satisfaction and social integration in Delta, Utah, that were originally analyzed by Brown, Geertsen, and Krannich in 1989. With 24 years of longitudinal data, we find that within approximately a decade of the boom period three of the four indicators returned to or exceeded pre‐boom levels. We argue that we need to modify our theories and vocabulary regarding boomtowns to account for a “boom‐bust‐recovery cycle” that better takes into consideration the dynamic nature of communities and their residents and how they subjectively adjust to shifts in objective conditions.

We theorize that people's perceptions of national hierarchy are aligned not only with longstanding cultural schemas of development but also with schemas of cultural wealth. We use data from the Nation Brands Index surveys to examine how European publics' evaluate their own country and other European countries across many attributes. We find that European publics rank northwest European countries highest on developmental attributes and southwestern European nations highest on cultural attributes, while they rank eastern European countries lowest in both categorizations. Moreover, we show that publics' rankings of countries load to two related yet distinct factors, the contents of which closely reflect schemas of development and cultural wealth. This evidence suggests that these two distinct schemas are simultaneously present in Europeans' perceptions of national hierarchy.

Diffusion of information in social network has been the focus of intense research in the recent past decades due to its significant impact in shaping public discourse through group/individual influence. Existing research primarily models influence as a binary property of entities: influenced or not influenced. While this is a useful abstraction, it discards the notion of degree of influence, i.e., certain individuals may be influenced “more” than others. We introduce the notion of attitude , which, as described in social psychology, is the degree by which an entity is influenced by the information. Intuitively, attitude captures the number of distinct neighbors of an entity influencing the latter. We present an information diffusion model (AIC model) that quantifies the degree of influence, i.e., attitude of individuals, in a social network. With this model, we formulate and study attitude maximization problem. We prove that the function for computing attitude is monotonic and sub-modular, and the attitude maximization problem is NP-Hard. We present a greedy algorithm for maximization with an approximation guarantee of ( 1 - 1 / e ) . In the context of AIC model, we study two problems, with the aim to investigate the scenarios where attaining individuals with high attitude is objectively more important than maximizing the attitude of the entire network. In the first problem, we introduce the notion of actionable attitude ; intuitively, individuals with actionable attitude are likely to “act” on their attained attitude. We show that the function for computing actionable attitude, unlike that for computing attitude, is non-submodular and however is approximately submodular . We present approximation algorithm for maximizing actionable attitude in a network. In the second problem, we consider identifying the number of individuals in the network with attitude above a certain value, a threshold. In this context, the function for computing the number of individuals with attitude above a given threshold induced by a seed set is neither submodular nor supermodular . We present heuristics for realizing the solution to the problem. We experimentally evaluated our algorithms and studied empirical properties of the attitude of nodes in network such as spatial and value distribution of high attitude nodes.