Experience sampling (ES) - also referred to as ecological momentary assessment (EMA) - is a data collection method that involves asking study participants to report on their thoughts, feelings, behaviors, activities, and environments in (or near) real time. ES/EMA is typically administered using an intensive longitudinal design (repeated assessments within and across days). Although use of ES/EMA is widespread in psychology and health sciences, uptake of the method among sociologists has been limited. We argue that ES/EMA offers key advantages for the investigation of sociologically relevant phenomena, particularly in light of recent disciplinary emphasis on investigating the everyday mechanisms through which social structures and micro (individual and relational) processes are mutually constitutive. We describe extant and potential research applications illustrating advantages of ES/EMA regarding enhanced validity, disentangling short-term dynamics, and the potential for linkage with spatially and temporally referenced data sources. We also consider methodological challenges facing sociological research using ES/EMA.

Social isolation is a potent predictor of poor health, mortality, and dementia risk. A great deal of research across national contexts provides causal evidence for these linkages and identifies key explanatory mechanisms through which isolation affects health. Research on social isolation recognizes that some people are more likely than others to be isolated, but over the past several decades, researchers have focused primarily on the consequences of isolation for health rather than a systematic assessment of the social conditions that foster isolation over the life course. In this article, we review the available evidence on inequities in social isolation and develop a conceptual framework to guide future research on structural systems that fuel social isolation over the life course. Future work in this area has the potential to identify root causes of inequality in social isolation, as well as targeted policy levers to reduce isolation in vulnerable populations.

This article reviews recent advances in causal inference relevant to sociology. We focus on a selective subset of contributions aligning with four broad topics: causal effect identification and estimation in general, causal effect heterogeneity, causal effect mediation, and temporal and spatial interference. We describe how machine learning, as an estimation strategy, can be effectively combined with causal inference, which has been traditionally concerned with identification. The incorporation of machine learning in causal inference enables researchers to better address potential biases in estimating causal effects and uncover heterogeneous causal effects. Uncovering sources of effect heterogeneity is key for generalizing to populations beyond those under study. While sociology has long emphasized the importance of causal mechanisms, historical and life-cycle variation, and social contexts involving network interactions, recent conceptual and computational advances facilitate more principled estimation of causal effects under these settings. We encourage sociologists to incorporate these insights into their empirical research.

Zoning determines what can be built where, and is ubiquitous in the United States. Low-density residential zoning predominates in US cities far more than in other countries, limiting housing opportunities for those who cannot afford large homes. These zoning regulations have racist and classist origins, make housing more expensive, and reinforce segregation patterns. While sociologists study these consequences of zoning, and other causes of unaffordable housing and segregation, they rarely examine zoning itself. This article argues for a sociological research agenda on zoning and land use.

Women's health, and what we know about it, are influenced by social factors. From the exclusion of women's bodies in medical research, to the silence and stigma of menstruation and menopause, to the racism reflected in maternal mortality, the relevance of social factors is paramount. After a brief history of research on women's health, we review selected patterns, trends, and inequalities in US women's health. These patterns reveal US women's poor and declining longevity relative to those in other high-income countries, gaps in knowledge about painful and debilitating conditions that affect millions of women, and deep inequalities that underscore the need to redress political and structural features of US society that enhance health for some and diminish it for others. We close by describing the challenges and opportunities for future research, and the promise of a social determinants of health approach for advancing a multilevel, intersectional, and biosocial understanding of women's health.

Concern over social scientists' inability to reproduce empirical research has spawned a vast and rapidly growing literature. The size and growth of this literature make it difficult for newly interested academics to come up to speed. Here, we provide a formal text modeling approach to characterize the entirety of the field, which allows us to summarize the breadth of this literature and identify core themes. We construct and analyze text networks built from 1,947 articles to reveal differences across social science disciplines within the body of reproducibility publications and to discuss the diversity of subtopics addressed in the literature. This field-wide view suggests that reproducibility is a heterogeneous problem with multiple sources for errors and strategies for solutions, a finding that is somewhat at odds with calls for largely passive remedies reliant on open science. We propose an alternative rigor and reproducibility model that takes an active approach to rigor prior to publication, which may overcome some of the shortfalls of the postpublication model.

Researchers have investigated the effects of ethnic heterogeneity on a range of socioeconomic and political outcomes. However, approaches to measuring ethnic diversity vary not only across fields of study but even within subfields. In this review, we systematically dissect the computational approaches of prominent measures of diversity, including polarization, and discuss where and how differences emerge in their relationships with outcomes of interest to sociologists (social capital and trust, economic growth and redistribution, conflict, and crime). There are substantial similarities across computations, which are often generalizations or specializations of one another. Differences in how racial and ethnic groupings are constructed and in level of geographic analysis explain many divergences in empirical findings. We conclude by summarizing the type of measurement technique preferred by outcome, when relevant, and provide considerations for future researchers contemplating how best to operationalize diversity. Finally, we highlight two less widely used yet promising measures of diversity.

Dramatic increases in criminal justice contact in the United States have rendered prison and jail incarceration common for US men and their loved ones, with possible implications for women's health. This review provides the most expansive critical discussion of research on family member incarceration and women's health in five stages. First, we provide new estimates showing how common family member incarceration is for US women by race/ethnicity and level of education. Second, we discuss the precursors to family member incarceration. Third, we discuss mechanisms through which family member incarceration may have no effect on women's health, a positive effect on women's health, and a negative effect on women's health. Fourth, we review existing research on how family member incarceration is associated with women's health. Fifth, we continue our discussion of the limitations of existing research and provide some recommendations for future research.

Despite decades of progress, the future of life expectancy in the United States is uncertain due to widening socioeconomic disparities in mortality, continued disparities in mortality across racial/ethnic groups, and an increase in extrinsic causes of death. These trends prompt us to scrutinize life expectancy in a high-income but enormously unequal society like the United States, where social factors determine who is most able to maximize their biological lifespan. After reviewing evidence for biodemographic perspectives on life expectancy, the uneven diffusion of health-enhancing innovations throughout the population, and the changing nature of threats to population health, we argue that sociology is optimally positioned to lead discourse on the future of life expectancy. Given recent trends, sociologists should emphasize the importance of the social determinants of life expectancy, redirecting research focus away from extending extreme longevity and towards research on social inequality with the goal of improving population health for all.

Fundamental Cause Theory (FCT) was originally proposed to explain how socioeconomic inequalities in health emerged and persisted over time. The concept was that higher socioeconomic status helped some people to avoid risks and adopt protective strategies using flexible resources - knowledge, money, power, prestige and beneficial social connections. As a sociological theory, FCT addressed this issue by calling on social stratification, stigma, and racism as they affected medical treatments and health outcomes. The last comprehensive review was completed a decade ago. Since then, FCT has been tested, and new applications have extended central features. The current review consolidates key in the literature in order to guide future research in the field. Notable themes emerged around types of resources and their usage, approaches used to test the theory, and novel extensions. We conclude that after 25 years of use, there remain crucial questions to be addressed.

While nearly three decades of "new immigrant destination" research has vastly enriched our understanding of diversity in contexts of reception within the United States, there is a striking lack of consensus as to the implications of geographic dispersion for immigrant incorporation. We review the literature on new destinations as they relate to ongoing debates regarding spatial assimilation and segmented assimilation; the influence of co-ethnic communities on immigrant incorporation; and the extent to which growth in immigrant populations stimulates perceived threat, nativism, and reactive ethnicity. In each of these areas, the sheer diversity of new destinations undermines consensus about their impact. Coupled with the continuous evolution in immigrant destinations over time, most dramatically but not limited to the impact of the Great Recession, we argue for the need to move beyond the general concept of "new destinations" and focus more directly on identifying the precise mechanisms through which the local context of reception shapes immigrant incorporation, where the historical presence of co-ethnic communities is but one of many dimensions considered, together with other labor, housing, and educational structures.

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: () social network analysis and group formation; () collective behavior and political sociology; () the sociology of knowledge; () cultural sociology, social psychology, and emotions; () the production of culture; () economic sociology and organizations; and () demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.

The U.S. Panel Study of Income Dynamics (PSID) celebrated its 50 anniversary in 2018. Initially designed to assess the nation's progress in combatting poverty, PSID's scope broadened quickly to a variety of topics and fields of inquiry. To date, sociologists are the second-most frequent users of PSID data after economists. Here, we describe the ways in which PSID's history reflects shifts in social science scholarship and funding priorities over half a century, take stock of the most important sociological breakthroughs it facilitated, in particular those relying on the longitudinal structure of the data, and critically assess the unique advantages and limitations of the PSID and surveys like it for today's sociological scholarship.

This review proposes that the end of life is a uniquely contemporary life course stage. Epidemiologic, technological, and cultural shifts over the past two centuries have created a context in which dying has shifted from a sudden and unexpected event to a protracted, anticipated transition following an incurable chronic illness. The emergence of an end-of-life stage lasting for months or even years has heightened public interest in enhancing patient well-being, autonomy, and the receipt of medical care that accords with patient and family members' wishes. We describe key components of end-of-life well-being and highlight socioeconomic and race disparities therein, drawing on fundamental cause theory. We describe two practices that are critical to end-of-life well-being (advance care planning and hospice) and identify limitations that may undermine their effectiveness. We conclude with recommendations for future sociological research that could inform practices to enhance patient and family well-being at the end of life.

Scholars have long looked to family composition to understand child well-being. Family instability, or the experience of repeated changes in parents' union status during childhood, represents a recent advance in this field that takes into account the dynamic nature of contemporary family organization and considers its implications for children's adjustment and development. We review some of the structural and cultural factors that have contributed to rising levels of family instability and highlight the emergence of national data to measure it. We then review the perspective that guides much of the scholarship on family instability and critically assess the contributions of this work to the understanding of child well-being. We close by suggesting new directions for research, with a call for work that broadens the conceptualization and measurement of contemporary children's family systems and home environments as well as the mechanisms that explain why-or whether-instability matters.

This review describes stress-related biological mechanisms linking interpersonal racism to life course health trajectories among African Americans. Interpersonal racism, a form of social exclusion enacted via discrimination, remains a salient issue in the lives of African Americans, and it triggers a cascade of biological processes originating as perceived social exclusion and registering as social pain. Exposure to discrimination increases sympathetic nervous system activation and upregulates the HPA axis, increasing physiological wear and tear and elevating the risks of cardiometabolic conditions. Consequently, discrimination is associated with morbidities including low birth weight, hypertension, abdominal obesity, and cardiovascular disease. Biological measures can provide important analytic tools to study the interactions between social experiences such as racial discrimination and health outcomes over the life course. We make future recommendations for the study of discrimination and health outcomes, including the integration of neuroscience, genomics, and new health technologies; interdisciplinary engagement; and the diversification of scholars engaged in biosocial inequities research.

We review research on institutions of redistribution operating in high-income countries. Focusing on the nonelderly, we invoke the concept of the household income package, which includes income from labor, from related households, and from the state. Accordingly, we assess three institutional arenas: predistribution (rules and regulations that govern paid work), private redistribution (interhousehold transfers), and conventional public redistribution (operating via cash transfers and direct taxes). In each arena, we assess underlying policy logics, identify current policy controversies, summarize contemporary cross-national policy variation, and synthesize existing findings on policy effects. Our assessment of redistributional effects focuses on three core socioeconomic outcomes: low pay, child poverty, and income inequality. We close by assessing how the three institutional arenas perform collectively and by calling for further work on how these institutions change over time and how they affect subgroups differentially.

For the past 80 years, social scientists have been linking historical censuses across time to study economic and geographic mobility. In recent decades, the quantity of historical census record linkage has exploded, owing largely to the advent of new machine-readable data created by genealogical organizations. Investigators are examining economic and geographic mobility across multiple generations, but also engaging many new topics. Several analysts are exploring the effects of early-life socioeconomic conditions, environmental exposures, or natural disasters on family, health and economic outcomes in later life. Other studies exploit natural experiments to gauge the impact of policy interventions such as social welfare programs and educational reforms. The new data sources have led to a proliferation of record linkage methodology, and some widespread approaches inadvertently introduce errors that can lead to false inferences. A new generation of large-scale shared data infrastructure now in preparation will ameliorate weaknesses of current linkage methods.

This article provides an overview of the integration of biomarkers and biological mechanisms in social science models of stratification and health. The goal in reviewing this literature is to highlight research that identifies the social forces that drive inequalities over the life course and across generations. The article is structured in the following way. First, descriptive background information on biomarkers is presented, followed secondly by a review of the general theoretical paradigms that lend themselves to an integrative approach. Third, the biomarkers used to capture several biological systems that are most responsive to social conditions are described. Fourth, research that explicates how social exposures "get under the skin" to affect physiological functioning and downstream health is discussed, using socioeconomic disadvantage as an illustrative social exposure. The review ends with emerging directions in the use of biomarkers in social science research. This article endeavors to encourage sociologists to embrace biosocial approaches in order to elevate the importance of social factors in biomedical processes and to intervene on the social conditions that create inequities.

References to the second demographic transition (SDT) concept/theoretical framework have increased dramatically in the last two decades. The SDT predicts unilinear change toward very low fertility and a diversity of union and family types. The primary driver of these changes is a powerful, inevitable and irreversible shift in attitudes and norms in the direction of greater individual freedom and self-actualization. First, we describe the origin of this framework and its evolution over time. Second, we review the empirical fit of the framework to major changes in demographic and family behavior in the U.S., the West, and beyond. As has been the case for other unilinear, developmental theories of demographic/family change, the SDT failed to predict many contemporary patterns of change/difference. Finally, we review previous critiques and identify fundamental weaknesses of this perspective, and provide brief comparisons to selected alternative approaches.

Despite their egalitarian ethos, schools are social sorting machines, creating categories that serve as the foundation of later life inequalities. In this review, we apply the theory of categorical inequality to education, focusing particularly on contemporary American schools. We discuss the range of categories that schools create, adopt, and reinforce, as well as the mechanisms through which these categories contribute to production of inequalities within schools and beyond. We argue that this categorical inequality frame helps to resolve a fundamental tension in the sociology of education and inequality, shedding light on how schools can-at once-be egalitarian institutions and agents of inequality. By applying the notion of categorical inequality to schools, we provide a set of conceptual tools that can help researchers understand, measure, and evaluate the ways in which schools structure social inequality.