Crowded Advocacy: Framing Dynamic in the Fracking Controversy in New York

In the hydrofracturing controversy in New York advocates hotly contested notions of the problem, what should be done, by whom, and how. This controversy can be characterized as “crowded advocacy,” involving intense mobilization and counter-mobilization of advocates with competing perspectives. Extant theories about the expansion of advocacy organizations are unclear about how advocates’ interactions shape the policy arena, particularly when there is competition within and across multiple coalitions. This article contributes by asking: How do advocates’ interactive framing dynamics shape public discourse when advocacy is crowded? It assumes that advocacy in general, and framing in particular, evolves as advocates respond to each other. I find that competing “discourse coalitions” collectively influence public discourse by articulating divergent notions of (1) what constitutes credible knowledge, (2) who can speak with authority on the issues, and (3) what institutional arrangements should be activated to manage risks. The consequence is that advocates have to react to others' framing on these issues—to defend their knowledge, their credibility, and specific institutions, rather than arguing their case on the merits. The implication is that advocacy is not only the means of influence (strategy) but also creates the context of advocacy in particular ways in a crowded field.     

Welfare State and Social Enterprise in Transition: Evidence from Serbia

This paper analyses welfare regime changes in Serbia and their impact on social enterprise development in the last two decades. We cover the period of significant transition-related reforms within the welfare state, with important implications on the position of these enterprises. Using data gathered from the qualitative field research, our study shows that there are two broad groups of factors that are important for development of the new generation of social enterprises, those that emerged in the last decade with an idea to foster entrepreneurial spirit and expanded into new domains other than those providing assistance to the marginalized groups. First, their decision to enter the social economy sector still depends on the environment created by the state. Secondly, their sustainability is affected by the factors typically found in any other enterprise of comparable scale like business skills, capacity to form networks and partner with relevant stakeholders.     

Elements of Capacity in Youth Development Nonprofits: An Exploratory Study of Urban Sport for Development and Peace Organizations

Organizational capacity is often discussed among nonprofit practitioners and scholars. Yet, empirical research employing a multidimensional capacity framework remains scarce in the nonprofit literature (Andersson et al. in VOLUNTAS Int J Volunt Nonprofit Organ 27(6):2860–2888, 2016). Using a qualitative research approach, we explored capacity in a specific segment of youth development nonprofits—sport for development and peace (SDP). We were guided by three research questions: (1) what are critical capacity elements of SDP nonprofits? (2) how do these capacity elements influence the ability of SDP nonprofits to achieve their desired goals and objectives? and (3) what are the capacity needs of SDP nonprofits in the USA? Findings from in-depth interviews with leaders of 29 organizations contribute to the development of theory on nonprofit capacity by providing a more nuanced understanding of capacity strengths and challenges related to broader nonprofit goal achievement. For example, paid staff, revenue generation, and internal infrastructure emerged as critically more important for capacity in this context. Practical and theoretical implications are further discussed.     

Transnational Information Politics and the “Child Migration Crisis”: Guatemalan NGOs Respond to Youth Migration

Sharp increases in “child migrants” from Central America detained at the US border in 2014 brought unprecedented levels of attention to long extant social and political issues perceived as causing youth migration. While governments on both sides of the US border faced criticism over responses to the migration “crisis,” the presumed causes of this migration presented in US media discourses went largely unquestioned. This article presents data collected in June 2015 from in-depth interviews with Guatemalan and transnational non-governmental organization (NGO) staff, scholars, lawyers, and activists in order to understand the complex interpretations of child migration by NGO actors in Guatemala. Findings illustrate how NGOs may selectively draw on the power of prevailing media narratives to buttress ideological and programmatic goals while simultaneously contesting how the same media depictions obscure the lived realities of migrants. We consider the transnational information politics of representations of “child migration” across government, media, and civil society sectors and the critical role of NGOs in articulating the complex realities faced by populations vulnerable to migration.     

NGO Strategies in an Authoritarian Context,and Their Implications for Citizenship: The Case of the People’s Republic of China

This study argues that different cities in China have different resource environments available for NGOs. Organizations react to these resource environments by constructing appropriate resource strategies, which in turn shape the characteristics and structures of the NGOs of that city. It further examines how these characteristics and structures influence the construction and performance of citizenship in an authoritarian environment. Specifically, some types of NGOs encourage Chinese citizens to be passive, while others offer a model for people to actively engage with social issues. This is aptly demonstrated in an analysis of NGOs operating across four cities—Beijing, Shanghai, Kunming, and Nanjing—which reveals three different types of resource environments and behavioral models for NGOs. We subsequently discuss the implications of each model for citizen engagement.     

Does Revenue Diversification Predict Financial Vulnerability Among Non-governmental Organizations in sub-Saharan Africa?

Non-governmental organizations (NGOs) in sub-Saharan Africa (SSA) experience financial challenges that hinder efforts to promote social change and development. Revenue diversification is one adaptive response to these challenges, yet there is a lack of evidence concerning the relationship between revenue diversification and financial vulnerability among NGOs in SSA. Using data from an online survey of NGOs (N = 170), we hypothesized that a greater number of revenue sources is associated with lower probability of financial vulnerability, while a greater level of dependence on international funding is associated with higher probability of financial vulnerability. Results from probit regression models controlling for organizational characteristics indicated partial support for hypotheses. Having four or more types of revenue was associated with 87% lower probability of financial vulnerability compared to having one type of revenue (p < 0.001). Also, NGOs with up to half of their budgets covered by international sources had 17% lower probability of financial vulnerability compared to NGOs with no international funding (p < 0.05). Implications for future research to further explore these relationships are discussed.     

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

Retrospective information on health status and its application for population health measures

Healthy life expectancies are almost always calculated by using health data from cross-sectional surveys. This type of calculation is done partly because data from longitudinal surveys are not always available, and when they are available, they are collected at intervals that are longer than one year. In such cases, collecting health information retrospectively for the years skipped by the survey is useful. The main purpose of this paper is to show how retrospective health information can be used to estimate life expectancies in different health states. Healthy life expectancies are estimated with and without using data on retrospective health information, and the corresponding estimates are compared. The two sets of estimates are similar. We conclude that retrospectively assessed health information based on a one-year recall period can be used to estimate years of life in various health states and that estimates based on such information will closely approximate estimates based on concurrent health information.