Testing the validity of social capital measures in the study of information and communication technologies

Social capital has been considered a cause and consequence of various uses of new information and communication technologies (ICTs). However, there is a growing divergence between how social capital is commonly measured in the study of ICTs and how it is measured in other fields. This departure raises questions about the validity of some of the most widely cited studies of social capital and ICTs. We compare the Internet Social Capital Scales (ISCS) developed by Williams [2006. On and off the ’net: scales for social capital in an online era. Journal of Computer-Mediated Communication, 11(2), 593–628. doi: 10.1111/j.1083-6101.2006.00029.x] – a series of psychometric scales commonly used to measure ‘social capital’ – to established, structural measures of social capital: name, position, and resource generators. Based on a survey of 880 undergraduate students (the population to which the ISCS has been most frequently administered), we find that, unlike structural measures, the ISCS does not distinguish between the distinct constructs of bonding and bridging social capital. The ISCS does not have convergent validity with structural measures of bonding or bridging social capital; it does not measure the same concept as structural measures. The ISCS conflates social capital with the related constructs of social support and attachment. The ISCS does not measure perceived or actual social capital. These findings raise concerns about the interpretations of existing studies of ‘social capital’ and ICTs that are based on the ISCS. Given the absence of measurement validity, we urge those studying social capital to abandon the ISCS in favor of alternative approaches.     

Can Psychosocial Intervention Improve Peer and Sibling Relations Among War‐affected Children? Impact and Mediating Analyses in a Randomized Controlled Trial

Social resources are considered important protectors in traumatic conditions, but few studies have analyzed their role in psychosocial interventions among war‐affected children. We examined (1) whether a psychosocial intervention (teaching recovery techniques, TRT) is effective in improving peer and sibling relations, and (2) whether these potentially improved relations mediate the intervention's impacts on children's mental health. Participants were 428 Palestinian children [10–13 (mean = 11.29, standard deviation SD = .68)‐year‐old girls (49.4 percent) and boys (50.6 percent)], who were cluster‐randomized into the TRT and wait‐list control groups. They reported the quality of peer (friendship and loneliness) and sibling (intimacy, warmth, conflict, and rivalry) relations, and posttraumatic stress, depressive and psychological distress symptoms, as well as psychosocial well‐being at baseline (T1), postintervention (T2), and six month follow‐up (T3). Results showed gender‐specific TRT intervention effects: Loneliness in peer relations reduced among boys and sibling rivalry reduced among girls. The TRT prevented the increase in sibling conflict that happened in the control group. The mediating hypothesis was partially substantiated for improved peer relations, and beneficial changes in sibling relations were generally associated with improved mental health.     

Bilateral Donors' Efforts to Assess and Manage UN Agencies' Effectiveness: Seeking a Balance between Paris Principles and Domestic Accountability

Since the turn of the century, results orientation and performance measurement have become buzzwords in development aid. Bilateral donors are increasingly concerned about the effectiveness of core‐funded UN specialised agencies, funds and programmes, through which they channel a substantial part of their funds. While the logic for increased monitoring is clear, it is less evident how to assess this information for purposes of accountability, performance‐based funding and governance. This article describes the general evolution in this area and discusses two major initiatives to harmonise and align bilateral assessments, using case‐study material from three bilateral donors (Belgium, the Netherlands and the UK) with clearly diverging performance‐management cultures, and exploring the extent to which they rely upon joint and aligned initiatives.     

The Determinants of Human Trafficking: A US Case Study

Human trafficking is a global problem. In this paper, I seek to find the determinants of international human trafficking by using the US as a case study. Previous studies have drawn primarily from the migration literature, proposing hypotheses that focus on economic factors, the level of democracy and other “push” factors in the countries of origin that create incentives for individuals to migrate. However, we know that international human trafficking is an involuntary form of migration and may be influenced by additional factors. I hypothesize that factors that influence the cost–benefit calculation of the trafficker determine the volume of human trafficking, in addition to the factors that affect the size of the pool of trafficking victims. I test my theory using the negative binomial regression model. My results indicate that while income inequality within a country and poor protection of women's rights are likely to produce a specific pool of victims, it is the reduction of operational costs for the trafficker that increases the number of individuals who are trafficked.     

Convergence rates for uniform confidence intervals based on local polynomial regression estimators

We investigate the convergence rates of uniform bias-corrected confidence intervals for a smooth curve using local polynomial regression for both the interior and boundary region. We discuss the cases when the degree of the polynomial is odd and even. The uniform confidence intervals are based on the volume-of-tube formula modified for biased estimators. We empirically show that the proposed uniform confidence intervals attain, at least approximately, nominal coverage. Finally, we investigate the performance of the volume-of-tube based confidence intervals for independent non-Gaussian errors.