Deconstructed and Constructive Logics: Explaining Inclusive Language Change in Queer Nonprofits, 1998-20161.

The United States is currently in the midst of a long, historic cultural transformation-redefining our collective representation to be inclusive of diverse sexual and gender identities. A core logic advancing this inclusion is to discursively recognize an expanded set of discrete, deconstructed identities-gay and lesbian expands to LGBT, LGBTQ, LGBTQIA1, and so on. But a newer logic stipulates that inclusion arises through using constructive identities that encompass many fluid experiences under a single term (e.g., "queer"). To understand inclusive change, the authors leverage a unique mesolevel site of cultural (re)production: service and advocacy nonprofit organizations. Using event history models, the authors investigate inclusive language change by 735 organizations from 1998 to 2016. They supplement analyses of administrative data with semistructured interviews with 13 nonprofit leaders, providing converging evidence. Findings showcase how bottom-up, horizontal, and top-down pressures explain both the inclusion of discrete identity labels and the shift to constructive logics.

Nonprofits: A Public Policy Tool for the Promotion of Community Subjective Well-being.

Looking to supplement common economic indicators, politicians and policymakers are increasingly interested in how to measure and improve the subjective well-being of communities. Theories about nonprofit organizations suggest that they represent a potential policy-amenable lever to increase community subjective well-being. Using longitudinal cross-lagged panel models with IRS and Twitter data, this study explores whether communities with higher numbers of nonprofits per capita exhibit greater subjective well-being in the form of more expressions of positive emotion, engagement, and relationships. We find associations, robust to sample bias concerns, between most types of nonprofit organizations and decreases in negative emotions, negative sentiments about relationships, and disengagement. We also find an association between nonprofit presence and the proportion of words tweeted in a county that indicate engagement. These findings contribute to our theoretical understanding of why nonprofit organizations matter for community-level outcomes and how they should be considered an important public policy lever.

Donations in social context.

Many nonprofit organizations rely on donations to fund their programs, and a robust literature predicts donations in large-scale quantitative studies. The focus, however, is almost exclusively on the financial characteristics of the organizations, leaving the social context underexplored. In this article, we theorize how ecological context, organizational identity, and social network ties can shape donations. We use the new Internal Revenue Service (IRS) release of e-filed nonprofit reporting forms to consider 95,518 501(c)3 nonprofits around 2015. Using lagged regression models, we find that organizations within a more favorable ecological context, those that use appeals to religion, and organizations with more volunteers report more donations. Furthermore, stressing affiliation with a geographic location is associated with more donations only under certain ecological conditions. The article concludes with a discussion of the implications of these results for nonprofit organizations and social theories regarding what influences donations to organizations.

Surviving Victimization: How Service and Advocacy Organizations Describe Traumatic Experiences, 1998-2016.

Service and advocacy organizations have long struggled to find the appropriate language to name traumatic experiences when working with vulnerable populations. Organizations have been pressed to adopt either "victim"-based language or "survivor"-based language, with both terms seen as having mutually exclusive meanings. However, despite academic and popular debates, no recent studies have documented trends in language used to describe traumatic experiences, whether of sexual and relationship violence, or of experiences of war, disaster, or major illness. In this research note, we use administrative data from the Internal Revenue Service to analyze how 3,756 service and advocacy organizations use trauma-related language between 1998 and 2016. Descriptive analysis shows that survivor language has been on the rise as victim language declined. Victim remains a common way to name trauma, however, and survivor tends to join, rather than displace, victim terminology. Further analysis also points to gendered use of both terms. Victim and survivor are used together most often in organizations that work with trauma experienced by women and in the field of sexual and relationship violence. We suggest these findings indicate a more complex story of how communities of language users emerge, which aligns with recent sociological treatments of discourse.

Can Government Intervention Increase Volunteers and Donations? Analyzing the Influence of VISTA With a Matched Design.

The United States has long relied on private organizations to provide public services to poor communities. However, while the federal government's support of the civic sector through grants and contracts is well studied, little research investigates how it subsidizes voluntary organizations through national service programs, such as Volunteers in Service to America (VISTA). In this article, we assess whether nonprofits that receive VISTA members show higher levels of donations and volunteers than matched nonprofits that did not receive VISTA members in the years following the Great Recession. We find that nonprofits that participated in the VISTA program had higher numbers of volunteers 2 years after participation, suggesting that national service was effective at supporting local organizations and building local civic infrastructure during an economic recovery. We also follow VISTA receiving organizations from 2010 to 2016 in a longitudinal design, finding a robust relationship of VISTA service and volunteering. These findings suggest VISTA is a resource for organizations and invite further research on the relationship between national service and anti-poverty work.

Does Use of Emotion Increase Donations and Volunteers for Nonprofits?

Nonprofits offer services to disadvantaged populations, mobilize collective action, and advocate for civil rights. Conducting this work requires significant resources, raising the question: how do nonprofits succeed in increasing donations and volunteers amid widespread competition for these resources? Much research treats nonprofits as cold, rational entities, focusing on overhead, the "price" of donations, and efficiency in programming. We argue that nonprofits attract donors and volunteers by connecting to their emotions. We use newly available administrative IRS 990 e-filer data to analyze 90,000 nonprofit missions from 2012 to 2016. Computational text analysis measures the positive or negative affect of each nonprofit's mission statement. We then link the positive and negative sentiment expressed by nonprofits to their donations and volunteers. We differentiate between the institutional fields of nonprofits-for example, arts, education, social welfare-distinguishing nonprofits focused on social bonding from those focused on social problems. We find that expressed positive emotion is often associated with higher donations and volunteers, especially in bonding fields. But for some types of nonprofits, combining positive sentiment with negative sentiment in a mission statement is most effective in producing volunteers. Auxiliary analyses using experimental and longitudinal designs provide converging evidence that emotional language enhances charitable behavior. Understanding the role of emotion can help nonprofit organizations attract and engage volunteers and donors.

Do National Service Programs Improve Subjective Well-Being in Communities?

Since the creation of Volunteers in Service to America (VISTA) in 1964 and AmeriCorps in 1993, a stated goal of national service programs has been to strengthen the overall health of communities across the United States. But whether national service programs have such community effects remains an open question. Using longitudinal cross-lagged panel and change-score models from 2005 to 2013, this study explores whether communities with national service programs exhibit greater subjective well-being. We use novel measures of subjective well-being derived from tweeted expressions of emotions, engagement, and relationships in 1,347 U.S. counties. Results show that national service programs improve subjective well-being primarily by mitigating threats to well-being and communities that exhibit more engagement are better able to attract national service programs. Although limited in size, these persistent effects are robust to multiple threats to inference and provide important new evidence on how national service improves communities in the United States.

Revisiting Declines in Social Capital: Evidence from a New Measure.

In the late twentieth century, researchers began calling attention to declining social capital in America and the potential consequences of this trend for a healthy society. While researchers empirically assessed the decline in social capital from the mid-1900s onward, this line of research diminished when the major source of data, the General Social Survey, stopped fielding critical questions in 2004. We do not know, therefore, whether social capital, especially associational social capital, has declined, stabilized, or even increased in a twentyfirst century America. In this paper, we develop a new measure of associational social capital using a confirmatory factor analysis of six indicators from the Civic Engagement Supplement to the Current Population Survey for 2008-2011 and 2013. Our findings support previous research suggesting that associational social capital does not seem to be declining over time. However, we do find evidence of a nonlinear decrease in associating during the Great Recession years. Across the entire time period, though, membership in groups has not declined and there has been little practical change in the amount of time that individuals spend with neighbors. Our analysis of the variance of social capital also shows no general change in the national dispersion of social capital from 2008 to 2013. The paper advances the measurement of social capital and updates our understanding of its possible decline.

Gender and Politics in the 2016 U.S. Election and Beyond.

We are delighted to introduce the Socius Gender and Politics Special Collection. The need for a special collection on gender and politics has never been timelier, evidenced both by gains in women's political participation and leadership around the world and the 2016 presidential election in the United States. Here, we introduce the timeliness of the topic with a review of the remarkable progress women have made in political representation over the past 150 years, a reiteration of the importance of women's political representation to democracy, and a brief discussion of the 2016 U.S. election cycle. We then introduce the eight papers that make up the special collection, emphasizing their contributions to ongoing debates in the field.

Women's rights in democratic transitions: A global sequence analysis, 1900-2012.

What determines countries' successful transition to democracy? This article explores the impact of granting civil rights in authoritarian regimes and especially the gendered aspect of this process. It argues that both men's and women's liberal rights are essential conditions for democratisation to take place: providing both women and men rights reduces an inequality that affects half of the population, thus increasing the costs of repression and enabling the formation of women's organising - historically important to spark protests in initial phases of democratisation. This argument is tested empirically using data that cover 173 countries over the years 1900-2012 and contain more nuanced measures than commonly used. Through novel sequence analysis methods, the results suggest that in order to gain electoral democracy a country first needs to furnish civil liberties to both women and men.

Does the standard voluntary association question capture informal associations?

Sociologists have long been attentive to participation in associational life. Yet, despite being repeatedly cautioned to consider more informal groups, most researchers focus on participation in formal voluntary associations using national surveys with fixed group categories, such as the General Social Survey (GSS). In this paper, we use new GSS data on the names of the voluntary associations listed by respondents to evaluate whether voluntary association prompts capture or miss various types of informal associations. We code the formality of the associations listed by respondents and also compare to a new sample of bottom-up, informal voluntary associations. We demonstrate that some response categories adequately capture both formal and informal associations, e.g., sports groups. However, our results also suggest that the standard voluntary association question both omits entire categories of informal associations and omits some informal variants of associations within categories. In the tradition of Baumgartner and Walker (1988), Wuthnow (1994), and Wellman et al. (2001), we suggest that we may misunderstand citizen associations if we ignore informal associating.

Murder, political resources, and women's political success.

This analysis tests overlooked sociological hypotheses about women's presence in the state legislatures and the House of Representatives. Stereotypes about women suggest that shifts in social conditions affect these political outcomes by making such stereotypes more or less salient. Findings indicate that beliefs about female competencies-such as women's purported unwillingness to endorse violent solutions-should reduce support for female candidates when increases in violent crime create demands for increasingly severe punishments. Since women also are typecast as being more protective of vulnerable populations than males, states with larger minority populations should have additional women in both legislatures. Pooled time-series models based on 1127 state-years show that fewer women were present in the state legislatures or in state delegations to the House after increases in the murder rates. States with larger minority populations, however, had more women in these two legislative bodies. Our results support claims that under researched social conditions produce political climates that either benefit or harm women who seek these offices.

Year of the Woman, Decade of the Man: trajectories of growth in women's state legislative representation.

The expansion of women's political representation ranks among the most significant trends in American politics of the last 100 years. In this paper, we develop two longitudinal theories to explain patterns of growth and change in women's state legislative representation over time. Gender salience suggests that years in which women's absence from politics is problematized (e.g., 1992-the Year of the Woman) will demonstrate higher levels of growth. Political climate suggests that periods in which domestic issues are stressed (e.g., the 1990s) will produce higher levels of growth than periods in which international issues are stressed (e.g., post 9/11). Combinations of these two theories create four possible trajectories of growth in women's representation that may be observed over time. We use latent growth curve models to assess the four theoretical trajectories, using data on women's state legislative representation from 1982 to 2006. We find that while women achieved fleeting success in the Year of the Woman, further gains were limited in the remainder of the 1990s and average growth stalled completely after 2001. Our results show futher that gender salience and, to a lesser extent political, climate matter to growth and change in women's political power over time.

An Empirical Evaluation of the Use of Fixed Cutoff Points in RMSEA Test Statistic in Structural Equation Models.

This article is an empirical evaluation of the choice of fixed cutoff points in assessing the root mean square error of approximation (RMSEA) test statistic as a measure of goodness-of-fit in Structural Equation Models. Using simulation data, the authors first examine whether there is any empirical evidence for the use of a universal cutoff, and then compare the practice of using the point estimate of the RMSEA alone versus that of using it jointly with its related confidence interval. The results of the study demonstrate that there is little empirical support for the use of .05 or any other value as universal cutoff values to determine adequate model fit, regardless of whether the point estimate is used alone or jointly with the confidence interval. The authors' analyses suggest that to achieve a certain level of power or Type I error rate, the choice of cutoff values depends on model specifications, degrees of freedom, and sample size.

The Noncentral Chi-square Distribution in Misspecified Structural Equation Models: Finite Sample Results from a Monte Carlo Simulation.

The noncentral chi-square distribution plays a key role in structural equation modeling (SEM). The likelihood ratio test statistic that accompanies virtually all SEMs asymptotically follows a noncentral chi-square under certain assumptions relating to misspecification and multivariate distribution. Many scholars use the noncentral chi-square distribution in the construction of fit indices, such as Steiger and Lind's (1980) Root Mean Square Error of Approximation (RMSEA) or the family of baseline fit indices (e.g., RNI, CFI), and for the computation of statistical power for model hypothesis testing. Despite this wide use, surprisingly little is known about the extent to which the test statistic follows a noncentral chi-square in applied research. Our study examines several hypotheses about the suitability of the noncentral chi-square distribution for the usual SEM test statistic under conditions commonly encountered in practice. We designed Monte Carlo computer simulation experiments to empirically test these research hypotheses. Our experimental conditions included seven sample sizes ranging from 50 to 1000, and three distinct model types, each with five specifications ranging from a correct model to the severely misspecified uncorrelated baseline model. In general, we found that for models with small to moderate misspecification, the noncentral chi-square distribution is well approximated when the sample size is large (e.g., greater than 200), but there was evidence of bias in both mean and variance in smaller samples. A key finding was that the test statistics for the uncorrelated variable baseline model did not follow the noncentral chi-square distribution for any model type across any sample size. We discuss the implications of our findings for the SEM fit indices and power estimation procedures that are based on the noncentral chi-square distribution as well as potential directions for future research.