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The triad census is an important approach to understand local structure in network science, providing The triad census is an important approach to understand local structure in network science, providing comprehensive assessments of the observed relational configurations between triples of actors in a network. However, researchers are often interested in combinations of relational and categorical nodal attributes. In this case, it is desirable to account for the label, or color, of the nodes in the triad census. In this paper, we describe an efficient algorithm for constructing the colored triad census, based, in part, on existing methods for the classic triad census. We evaluate the performance of the algorithm using empirical and simulated data for both undirected and directed graphs. The results of the simulation demonstrate that the proposed algorithm reduces computational time by approximately many-fold over the naive approach. We also apply the colored triad census to the Zachary karate club network dataset. We simultaneously show the efficiency of the algorithm, and a way to conduct a statistical test on the census by forming a null distribution from 1,000 realizations of a mixing-matrix conditioned graph and comparing the observed colored triad counts to the expected. From this, we demonstrate the method's utility in our discussion of results about homophily, heterophily, and bridging, simultaneously gained via the colored triad census. In sum, the proposed algorithm for the colored triad census brings novel utility to social network analysis in an efficient package.comprehensive assessments of the observed relational configurations between triples of actors in a network. However, researchers are often interested in combinations of relational and categorical nodal attributes. In this case, it is desirable to account for the label, or color, of the nodes in the triad census. In this paper, we describe an efficient algorithm for constructing the colored triad census, based, in part, on existing methods for the classic triad census. We evaluate the performance of the algorithm using empirical and simulated data for both undirected and directed graphs. The results of the simulation demonstrate that the proposed algorithm reduces computational time by approximately many-fold over the naive approach. We also apply the colored triad census to the Zachary karate club network dataset. We simultaneously show the efficiency of the algorithm, and a way to conduct a statistical test on the census by forming a null distribution from 1; 000 realizations of a mixing-matrix conditioned graph and comparing the observed colored triad counts to the expected. From this, we demonstrate the method's utility in our discussion of results about homophily, heterophily, and bridging, simultaneously gained via the colored triad census. In sum, the proposed algorithm for the colored triad census brings novel utility to social network analysis in an efficient package.

Mixed effects multilevel models are often used to investigate cross-level interactions, a specific type of context effect where an upper-level variable moderates the association between a lower-level predictor and the outcome. We argue that multilevel models involving cross-level interactions should always include random slopes on the lower-level components of those interactions. Failure to do so will usually result in severely anticonservative statistical inference. Monte Carlo simulations and illustrative empirical analyses of the European Social Survey suggest that models omitting the random slope will underestimate true standard errors on cross-level interaction terms and the main effects of lower-level components by 30 to 50 percent in typical applications. Many practitioners seem to be unaware of these issues. Roughly half of the cross-level interaction estimates published in the European Sociological Review between 2011 and 2016 are based on models that omit the crucial random slope term. Detailed analysis of the associated test statistics suggests that many of the estimates would not meet conventional standards of statistical significance if estimated using the correct specification. This raises the question how much robust evidence of cross-level interactions sociology has actually produced over the past decades.

The relationship between homeland states and their diasporic subjects abroad has been a subject of social scientific inquiry on both sides of the Atlantic (Dufoix 2008; Smith 2003). Scholars from various disciplinary perspectives have put forth theories of why homeland states engage with emigrant or coethnic populations, and why these populations seek to engage with the government of their homeland. What is missing in the literature is a theory of how such homeland-diaspora relationships come into being and how they change over time. Understanding the development of homeland-diaspora relationships is crucial for making sense of migrant transnationalism and of state sovereignty in a globalized era. This study addresses this gap in the literature through a historical and ethnographic study of the relationship between the Republic of China (ROC) and Chinese language schools in Los Angeles. The case of the ROC and the Chinese diaspora is an illuminating case because the anomalous nature of the ROC’s political status calls into question many of the main assumptions in the existing literature. In particular, it challenges the assumption that each diaspora corresponds to a sole, legitimated homeland state. In the Chinese case, the geopolitical divisions at the end of the Chinese Civil War resulted in two states: the People’s Republic of China (PRC) on the Chinese mainland and the ROC on the island of Taiwan. While the communist PRC was not geopolitically legitimate in the West during the early part of the Cold War, widespread recognition of the PRC in the 1970s has left the ROC’s statehood claim in a liminal state. For the diaspora, this has resulted in two potential homeland states. The ROC’s de-legitimated claim to statehood has left it dependent on diaspora political support just as demographic shifts and transformations in the US social and political environment made it easier for the diaspora to support the PRC. I argue that the balance of power between the ROC diaspora bureau and the language schools have transformed since the Cold War as a result of domestic and geopolitical changes. The key factor shaping this relationship is the presence of the PRC and its changing geopolitical role since the 1980s. My explanation bridges theories of migrant transnationalism with theories of resource dependence among hierarchically linked organizations. This study contributes to the literatures on immigration, nationalism, and ethnicity, but also to broader literatures on borders and the reach of the state.

This paper explores a sociological problem born of the following axioms:1) Individuals, their circumstances and their interactions are heterogeneous and subject to constant change;2) Individuals and their interactions make up groups;3) Groups are normally very stable, lacking change.After defining social stability and reviewing current rational choice theorizing, this paper contends that neither past nor current sociological thinking sufficiently explains how social stability can come from the arbitrariness of individual interactions. It then posits that all choices have accompanying ‘entrained' choices, subsumed to conscious decision-making, one being for ‘predictability’; a ubiquitous yet useful characteristic of sociodynamics that addresses the problem above in a testable, falsifiable way, and could be a sociological ‘constant’ for use in further research.

Ethnographers often study those who periodically meet to interact in multiple venues. This article focuses on how people who share and engage in tasks in recurrently-visited venues define and change their social projects’ problems and solutions. To address the complexities of this “meta-work,” I introduce the concept of “tethers.” Tethers are links across venues that people use to set and shift these problems and solutions that are continuously being contested. Drawing on examples from the author’s fieldwork and other ethnographic accounts of professional work, I examine three types of tethers: focal participants, things, and language. Paying attention to tethers also results in practical implications for taking fieldnotes, timing observations, and choosing fieldsites. I argue that a focus on subjects’ use of tethers across venues helps mitigate the challenges ethnographers face when accounting for the influence of temporally and geographically distant sites of recurrent interaction.

Researchers increasingly use correspondence audit studies to study racial/ethnic discrimination in employment, housing, and other domains. Although this method provides strong causal evidence of racial/ethnic discrimination, these claims depend on the signal being clearly conveyed through names. Few studies have pretested individual racial and ethnic perceptions of the names used to examine discrimination. The author conducts a survey experiment in which respondents are asked to identify the races or ethnicities they associate with a series of names. Respondents are provided with combinations of Hispanic and Anglo first and last names. Hispanic first names paired with Anglo last names are least likely to be recognized as Hispanic, while all versions of Hispanic first and last names are highly recognized (≥90 percent). The results suggest that researchers must use caution when trying to signal Hispanic ethnicity in experiments, and prior findings from correspondence audits may be biased from poor signals.

How do European service sector workers evaluate their quality of work and life nowadays? Europeanization and globalization are bringing about major shifts in the economy, but we know little about how this is affecting the well-being of Europe’s citizens. This chapter presents a range of subjective indicators for the quality of work and life as reported by service sector employees in eight European countries. In addition, it provides background information on the organizational context. The countries involved are at different stages of economic development and have differing welfare systems. Four organizations were surveyed in each country: one bank or insurance company, one public hospital, one retail organization and one IT or telecom company.

Policies that admit immigrants based on their education have dramatically reshaped the demographics of the United States and Canada. In the mid-1960s, facing pressures to open their borders to non-Europeans, both countries replaced previous policies of racial and nationality discrimination with new systems of socioeconomic discrimination. These policies explain the growth of Asian immigration from the 1970s onward, as well as the high levels of education among Asian immigrants and their descendants. Refugees and family migrants, however, added socioeconomic diversity. Recent developments in skilled immigrant selection programs will continue to shape Asian American and Asian Canadian demographics in the future.

One of the great lessons from the last half century of research on social networks is that relationships are constantly in flux. While much social network analysis focuses on static relationships between actors, there is also a rich tradition of work extending back to foundational studies in network science focused on the notion that network change is an indelible aspect of social life for human and non-human actors alike (e.g., Bott, 1957; Heider, 1946; Newcomb 1961; Rapoport, 1949; Sampson, 1969). Today, social network researchers benefit from this history in that a host of methods to collect and analyze such dynamic network data have been developed. Among them, the methods based on stochastic process theory have given rise to a paradigm where inferences and predictions can be made on the mechanisms that drive changes in social structure.

The literature on civil resistance finds that nonviolent campaigns are more likely to succeed than violent insurgencies. A parallel literature on democratization poses mass mobilization as exogenous to political liberalization. Contributing to both literatures, we propose the category of unarmed collective violence to capture an empirically recurring form of unruly collective action, and use a mixed methods research design to examine its impact on democratization. An event history analysis finds that riots are positively associated with political liberalization in 103 nondemocracies from 1990 to 2004. Attacks by civilians on police stations during the 25th January Egyptian Revolution, which disrupted the coercive capacity of the Mubarak regime, illustrate one way in which unarmed collective violence can bring about a democratic breakthrough. A qualitative examination of all 80 democratic transitions held between 1980 and 2010 also reveals the salience of unarmed collective violence. These findings contribute to research on the dynamics of contentious democratization, and suggest that remaining unarmed may be more consequential for a democracy campaign than adhering to nonviolence.

Paper read at the 61st meeting of Japan Association for Mathematical Sociology. This paper criticizes International Fertility Decision-making Study (IFDMS) about its validity and comparability, mainly based on the Japanese version questionnaire.

Since its very inception, the European Sociological Review has encouraged “cross-national comparative work which concentrates on or includes European societies” (Mayer, Goldthorpe, and Ringen, 1985). Although our focus is not only merely on papers of a cross-national nature, we have published a considerable number of such studies. Another aim of ESR is to further the more general development of sociology by publishing theoretical and methodological articles where these have a direct relevance for sociological research. A recent example of a prominent methodological study in ESR was the 2010 article by Carina Mood, which has—judging from the over 200 citations it has already received in SSCI-listed journals alone—had considerable impact on the way logistic regression is practiced (or not) in contemporary social science research.

In this paper we combine the extensive literature on the analysis of life course trajectories as sequences with the literature on causal inference, and propose a new matching approach to investigate the causal effect of the timing of life course events on subsequent outcomes. Our matching approach takes into account pre-event confounders that are both time-independent and time-dependent, as well as life course trajectories. After matching, treated and control individuals can be compared using standard statistical tests or regression models. We apply our approach to the study of the consequences of the age at retirement on subsequent health outcomes, using a unique dataset from Swedish administrative registers. Once selectivity in the timing of retirement is taken into account, effects on hospitalization are small, while early retirement has negative effects on survival. Our approach also allows for heterogeneous treatment effects. We show that the effects of early retirement differ according to pre-retirement income, with higher income individuals tending to benefit from early retirement, while the opposite is true for individuals with lower income.

Our aim here is to plead for the significance of cultural considerations of overlapping inter—attitudinal patterns right next to well established structural considerations of interorganizational networks based on overlapping membership patterns. In particular, we examine how the analytic methodological incorporation of cultural attributes or attitudes might enhance our understanding of structural community categorizations in interorganizational networks. For this purpose, we analyze data of the International Peace Protest Survey (IPPS) on the world—wide peace protests of February, 15, 2003, in or- der to manifest the added value offered by the consideration of the culture- structure duality in participation studies.

Social influence plays an important role in human behavior and decisions. Sources of influence can be divided as external, which are independent of social context, or as originating from peers, such as family and friends. An important question is how to disentangle the social contagion by peers from external influences. While a variety of experimental and observational studies provided insight into this problem, identifying the extent of contagion based on large-scale observational data with an unknown network structure remains largely unexplored. By bridging the gap between the large-scale complex systems perspective of collective human dynamics and the detailed approach of social sciences, we present a parsimonious model of social influence, and apply it to a central topic in political science--elections and voting behavior. We provide an analytical expression of the county vote-share distribution, which is in excellent agreement with almost a century of observed U.S. presidential election data. Analyzing the social influence topography over this period reveals an abrupt phase transition from low to high levels of social contagion, and robust differences among regions. These results suggest that social contagion effects are becoming more instrumental in shaping large-scale collective political behavior, with implications on democratic electoral processes and policies.

We first discuss the centrality of data paradigms in demography, documenting their rise and fall over time also making use of Google Books Ngram Viewer. We then move on to discuss the undergoing ``Data Revolution'' in demography, with a focus on emerging forms of big data access and on the use of digital breadcrumbs.

This paper proposes a post-positivist methodological approach to describe the dynamics of a flow of social events that evolve under the existing specific conditions in a set of social structures, relying on the epistemological assumptions of Critical Realism. This philosophy of science stance suggests case study as the preferred research strategy to explain such complex, dynamic and context-sensitive social phenomena. The contribution of this work is to propose the general idea of a process tracing methodology for multiple cases study relying on a qualitative sequence analysis procedure and a discrete, rule-based mathematical model deduced from the Generative Grammar Theory. It can describe the sequential patterns of events analytically based on the prior theoretical propositions and the observed empirical facts. The occasional divergences of some facts with such model lead to necessary modifications on the descriptive propositions of a process-like social phenomenon to achieve greater level of explanatory power.

Over the last several decades, dozens of authoritarian regimes have fallen and been replaced by formal democracies. These new democracies are not all of identical quality--some have made substantially greater progress than others towards deepening democratic institutions. We make use of a new dataset which identifies five distinct dimensions of democratization in order to study this variation. We argue that prolonged unarmed contentious mobilization prior to transition drives democratic progress in each of these five dimensions. Mobilization matters because it generates a new, democratically-oriented political elite and because it furnishes non-elites with the capacity for autonomous collective action. In panel regressions spanning the 1950 to 2010 period and using original data, we show that the duration of antecedent anti-authoritarian mobilization is a significant and consistent predictor of subsequent democratic deepening. To illustrate the mechanisms, we present a historical analysis of democratic transition in Brazil. This case study shows how both formal political actors and non-elite collective actors, emboldened by prolonged mobilization, drove deepening of democracy post-transition.

SUMMARYIn the days following the publication of a Washington Post article that detailed allegations of sexual abuse against Roy Moore, Emerson College Polling released an election poll of Alabama voters that showed Moore maintaining a 10-point lead over his opponent Doug Jones. The Emerson College Poll was conducted using survey data administered by landline phone and over the internet. In this working paper, I analyze raw data from this poll and find irregularities in the internet sample that might suggest that the respondents were not properly sampled by the data vendor that administered the survey, Opinion Access Corp. Specifically, a substantial number of respondents in the internet sample were unable to accurately match their county of residence to their US congressional district when presented with a map of Alabama which displayed both (Figure 2). The misclassification rate for the internet sample was 36% (117 respondents out of 324). Such a high misclassification rate might indicate that some of the respondents in the sample did not reside in Alabama.Although the aim of this paper is not to predict the outcome of an electoral contest, the removal of this poll from aggregate polling averages might indicate a tighter Alabama senate race than previously understood. Emerson College Polling released an additional poll that surveyed support for Roy Moore and Doug Jones in the Alabama senate race on November 28, 2017 that similarly relied on respondents acquired through Opinion Access Corp. If the same irregularities observed in the November 13, 2017 poll are present in the more recent poll, then political observers should interpret the results with the understanding that a substantial number of respondents interviewed might be invalidly included. As researchers increasingly rely on internet data vendors to acquire respondents for polls and surveys, I argue for the necessity of proactively verifying the accuracy of third-party data. With the use of survey “attention checks,” researchers can determine whether data vendors have provided samples that match their requested sampling frame and gain confidence in the validity of their results.

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac)."

The “elitist approach” to democratization contends that “democratic regimes that last have seldom, if ever, been instituted by mass popular actors” (Huntington 1984:212). This article subjects this observation to empirical scrutiny using statistical analyses of new democracies over the past half-century and a case study. Contrary to the elitist approach, I argue that new democracies growing out of mass mobilization are more likely to survive than are new democracies that were born amid quiescence. Survival analysis of 112 young democracies in 80 different countries based on original data shows that the longer the mobilization, the more likely the ensuing democracy is to survive. I use a case study of South Africa to investigate the mechanisms. I argue that sustained unarmed uprisings have generated the longest-lasting new democracies—largely because they are forced to develop an organizational structure, which provides a leadership cadre for the new regime, forges links between the government and society, and strengthens checks on the power of the post-transition government.

This paper explores the issue of temporality in undertaking ethnographic fieldwork, drawing on research that examined urban automated management, wherein software is used to automatically regulate traffic flow in a city. In this case, the study addressed: 1) polyrhythmia at different scales produced by algorithms, technology, management and urban life, and; 2) the process of organizing multiple timelines to tune the ‘heartbeat’ of the city. Time is a resource for coordination and regulation, as well as for making sense of actions and experience. Being increasingly dispersed, and black-boxed in a multiplicity of processes affecting and configuring the way the past, present and future are perfomed and lived, time also represents a new object of concern for the ethnographic investigation of algorithmic management. I argue that ethnography allows us to understand the material organizing of dispersed and heterogeneous temporalities while also intersecting with such temporalities. Drawing on Guattari and Deleuze’s concept of ‘refrain’ and from Lefebvre’s ‘rhythmanalysis’, I introduce the concepts of rhythm-making and halfway ethnography with the purpose of accounting for the manufacturing of multiple temporalities and for the time-boundedness that links ethnographic practice and the technological, organizational, and cultural ‘heartbeats’ of fieldwork. This approach intends to temporally and spatially reposition organizational ethnography, offering analytical tools to study new contemporary entanglements of ethnographic practice and data.

Unpaid or ‘free’ labour is an important element of how precarity has been theorized. It is also an issue that is often seen as endemic to cultural and creative work, rightly attracting a range of criticism. Questions as to the role of unpaid work, for example internships, have become central to understanding the social exclusiveness of many cultural and creative jobs. This paper develops this existing analysis by comparing and contrasting the meaning of 'free' work over the life course of a range of creative occupations, historicising the impact of unpaid labour on the creative sector and showing how it has been stratified by social class, age and career stage. The paper uses two datasets drawn from the Panic! What happened to social mobility in the arts? project, to outline the differing experiences of unpaid labour in cultural and creative occupations. By demonstrating the stratification of unpaid work as a form of precariousness in cultural jobs, along with the social distribution of benign narratives of unpaid work, the paper aims to offer new empirical evidence for those seeking to resist precarious forms of labour.

Συνήθως διαπιστώνεται μια μεγάλη απόσταση ανάμεσα στον αγώνα για τη χειραφέτηση της εργατικής τάξης και στην έρευνα που παράγεται στα πανεπιστημιακά πλαίσια. Ακόμα και αν, ως κοινωνική, η έρευνα έχει ως αντικείμενο τις συνθήκες εργασίας και ζωής της εργατικής τάξης, ο συνηθισμένος κανόνας είναι η αντικειμενοποίηση των υποκειμένων της τάξης, η εξουδετέρωση της κίνησης και της δράσης τους, η εξ-ουδετέρωση της δράσης και της κίνησης των ερευνητών, η απομάκρυνση ή δεοντική απαγόρευση της όποιας προοπτικής συνεργασίας, συν-έρευνας, ή κοινών συμφερόντων ερευνητών - ερευνώμενωνi. Στο άρθρο λοιπόν αυτό θα υπάρξει μια προσπάθεια για μια ενδεικτική επισκόπηση των μονοπατιών που συνδυάζουν την ερευνητική επιστημονική προσπάθεια με τον χειραφετητικό αγώνα.

Comparative political science has long worried about the performance of multilevel models when the number of upper-level units is small. Exacerbating these concerns, an influential Monte Carlo study by Stegmueller (2013) suggests that frequentist methods yield biased estimates and severely anti-conservative inference with small upper-level samples. Stegmueller recommends Bayesian techniques, which he claims to be superior in terms of both bias and inferential accuracy. In this paper, we reassess and refute these results. First, we formally prove that frequentist maximum likelihood estimators of coefficients are unbiased. The apparent bias found by Stegmueller is simply a manifestation of Monte Carlo Error. Second, we show how inferential problems can be overcome by using restricted maximum likelihood estimators for variance parameters and a t-distribution with appropriate degrees of freedom for statistical inference. Thus, accurate multilevel analysis is possible without turning to Bayesian methods, even if the number of upper-level units is small.

Social comparison theory predicts that unemployment should be less distressing when the experience is widely shared, but does this prediction extend beyond the unemployed to those who are at risk of job loss? Research demonstrates a link between aggregate unemployment and employed individuals’ perceptions of job insecurity; however, less is known about whether the stress associated with these perceptions is shaped by others’ unemployment experiences. We analyze a nationally representative sample of Canadian workers (CAN-WSH study; N=3,900) linked to census data, and test whether regional unemployment influences the mental health consequences of job insecurity. Multilevel analyses provide more support for the social norm of insecurity hypothesis over the amplified threat hypothesis: the health penalties of job insecurity are weaker for individuals in high unemployment regions. This contingency is partially explained by the ability of insecure workers in poor labor market contexts to retain psychological resources important for protecting mental health.

The use of assisted reproductive technology (ART) is widespread, with an estimated five million ART-conceived children born now worldwide. Despite this marked increase in the use of ART, little is known about the demographic consequences. We explore several dimensions of demographic consequences of ART. The proportion of ART-conceived babies varies greatly across countries, and our analyses suggest that ART costs, policies and regulations, and national norms and values are core determinants of these differences. Based on a review of the literature, we conclude that ART has a negligible impact on national fertility rates, thereby suggesting that it is not an effective policy instrument to counter low fertility. Furthermore, we show that the recent increase in twin births in Europe can be attributed to ART usage. A case study of Italy reveals that ART mothers were more likely to deliver prematurely, even when controlling for maternal age.