Stigma, HIV/AIDS and prevention of mother-to-child transmission in Zambia

This report evaluates the extent of perceived and enacted HIV/AIDS-related stigma in a rural setting in Zambia. Stigmatisation is abundant, ranging from subtle actions to the most extreme degradation, rejection and abandonment. Women with HIV and pregnant women assumed to be HIV positive are repeatedly subjected to extensive forms of stigma, particularly once they become sick or if their child dies. Despite increasing access to prevention of mother to child transmission initiatives, including anti-retroviral drugs, the perceived disincentives of HIV testing, particularly for women, largely outweigh the potential gains from available treatments. HIV/AIDS related stigma drives the epidemic underground and is one of the main reasons that people do not wish to know their HIV status. Unless efforts to reduce stigma are, as one peer educator put it, “written in large letters in any HIV/AIDS campaign rather than small”, stigma will remain a major barrier to curbing the HIV/AIDS pandemic.     

Social network effects on academic achievement

How peer groups contribute to educational outcomes has long interested researchers. However, the possibility that peer groups dominated by either low- or high-achieving youth can have substantively different effects on achievement has been largely ignored. In this paper, we show that while being embedded in a high-achieving network of friends is not associated with increased own achievement, being embedded in a low-achieving network is associated with decreased own achievement. In additional analyses, we present evidence that these associations are at least in part due to influence, as opposed to only selection effects or shared environment. We also examine whether the structure of the network in which a student is embedded might affect their educational achievement. We show that achieving at higher levels positively predicts how centrally located a student is in their network, but being more centrally located does not predict concurrent achievement. This finding suggests that the behavior of individuals is affecting the formation of network structure and not the reverse.     

MEASURING THE INTERDEPENDENCE OF MULTINATIONAL FIRMS' FOREIGN INVESTMENTS

Earlier work found evidence for geographic linkages of aggregate foreign direct investment across countries and country‐pairs. From a theoretical point of view, such linkages at the macroeconomic level may root in between‐firm as well as within‐firm linkages and originate from information spillovers across or within firms in exploring unknown markets, and vertical linkages between production plants across different locations within the firm. We use data on the universe of German multinational enterprises (MNEs) to empirically explore how marginal investments at one foreign affiliate depend on investments at other affiliates within the same MNE. The empirical approach employs two channels or modes of cross‐affiliate interdependence: mere geography (capturing horizontal linkages through correlated learning and horizontal competition within the firm) and input–output relationships within or across industries (which capture vertical linkages). Adding to earlier findings at the aggregate level, we find evidence of a significant interdependence of investments within the firm. In the firm‐level data at hand, vertical linkages appear to be more important than horizontal ones. Investments at one location tend to stimulate investments at other locations of the same MNE, particularly if input linkages are strong. The opposite seems to be true for output linkages. Beyond vertical linkages, mere geographic proximity matters only to a minor extent. This suggests that evidence of linkages through geographic closeness at aggregate data levels accrue mainly to reasons of vertical linkages within networks of affiliates. (JEL C31, D22, F21, F23, F68, G31, H32)     

Identifying radon-prone building typologies by marginal modelling

Radon is a naturally occurring decay product of uranium known to be the main contributor to natural background radiation exposure. It has been established that the health risk related to radon exposure is lung cancer. In fact, radon is considered to be a major leading cause of lung cancer, second only to smoking. In this paper, we identified building typologies that affect the probability of detecting indoor radon concentration above reference values, using the data collected within two monitoring campaigns recently conducted in Northern Italy. This information is fundamental both in prevention, i.e. when the construction of a new building is planned and in mitigation, i.e. when a high concentration detected inside buildings has to be reduced. A spatial regression approach for binary data was adopted for this goal where some relevant covariates on the soil were retrieved by linking external spatial databases.     

Pandemic Recovery Analysis Using the Dynamic Inoperability Input-Output Model

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model^{( 1 , 2 )} and the dynamic inoperability input-output model (DIIM).^{( 3 )} These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.     

Relationships among JIT practices: an interpretive modeling approach

Abstract

This research develops a model of relationships among components of Total-JIT, including JIT-information, JIT-manufacturing, JIT-purchasing, and JIT-selling, to establish an implementation hierarchy based on relative importance. The data collected relates to the relationships among JIT components and two performance measures, supply chain competency and organizational performance. Two groups are used in the research, one group of five operations management academics and another group of 30 practicing operations managers working in U.S. manufacturing firms. An interpretive structural modelling methodology is used to develop alternative structural models. The academics’ data show JIT-information emerging as lynchpin of relationships, directly impacting all other JIT practices and both performance measures. The practitioners’ data indicates that all JIT practices and performance measures are interactive as components and outcomes. This study is the first to apply interpretive structural modelling to investigate the interplay among total-JIT components and the performance measures of supply chain competency and organizational performance.     

Developing a Cross-National Comparative Framework for Studying Labour Market Segmentation: Measurement Equivalence with Latent Class Analysis

Social Indicators Research - This article proposes a novel measurement model of labour market segmentation in Europe for cross-national comparisons, tackling three drawbacks of current approaches:...     

“I Am Becoming More and More Like My Eldest Brother!”: The Relationship Between Older Siblings,Adolescent Gambling Severity,and the Attenuating Role of Parents in a Large-Scale Nationally Representative Survey Study

The present study examined the association between having older siblings who gamble and adolescent at-risk/problem gambling and how parents (i.e., parental knowledge of their whereabouts) and peers might moderate such effects. Data were drawn from the ESPAD^®Italia2012 survey (European School Survey Project on Alcohol and Other Drugs) comprising a nationally representative Italian sample of adolescents. The analysis was carried out on a subsample of 10,063 Italian students aged 15–19 years (average age = 17.10; 55 % girls) who had at least one older sibling and who had gambled at some point in their lives. Respondents’ problem gambling severity, older gambler sibling, gambler peers, parental knowledge, and socio-demographic characteristics were individually assessed. Multinomial logistic regression analyses including two- and three-way interactions were conducted. The odds of being an at-risk/problem gambler were higher among high school students with older siblings that gambled and those with peers who gambled. Higher parental knowledge (of who the adolescent was with and where they were in their leisure time) was associated with lower rates of at-risk/problem gambling. There was also an interaction between gamblers with older siblings and parental knowledge. The combination of having siblings who gambled and a greater level of parental knowledge was associated with lower levels of problem gambling. The present study confirmed the occurrence of social risk processes (older siblings and peers who gambled) and demonstrated that gambling among older siblings and peers represents an important contextual factor for increased at-risk/problem gambling. However, parental knowledge appears to be sufficient to counterbalance the influence of older siblings.