With the necessity of having a college degree to participate in todays society, there is increased pressure on young people to enroll in college and become fully functioning, independent members of society. The financial toll that college takes on students has created a need for students whose parents cannot pay their full tuition or have financial aid cover the costs to step up to fill the economic gap. This has created two distinct groups of college students- those who work and those who do not. By analyzing the time use activities of each group, this research shows that working students spend less time on most activities. Each hour that a student spends working causes a deduction in time that they spend on class, homework, and sleeping.

Scant information is available on experiences with language among immigrant populations in new destinations. This study provides a multi-dimensional portrait of the linguistic incorporation of Dominican immigrants in the majorityminority city of Reading, Pennsylvania. The results show that daily life for most largely occurs in a Spanish-language milieu, but English proficiency and use in social networks is primarily a function of exposure to the United States. This is consistent with the standard narrative of assimilation models. At the same time, negative experiences with the use of both English and Spanish suggest that the linguistic context of reception is inhospitable for a substantial share of this population. Negative experiences with English are particularly likely to be mentioned by those with dark skin and greater cumulative exposure. Lastly, language plays an important role in experiences with ethno-racial enmity more broadly. Nonetheless, the persistent effect of skin tone indicates that such experiences are not reducible to language per se.

El presente artículo tiene como objetivo analizar el problema de la subutilización de las capacidades de la población profesional mexicana, tanto en su país de origen como en los Estados Unidos, con especial hincapié en aquellos formados en las áreas de las ciencias, la tecnología, las ingenierías y las matemáticas (CTIM). El argumento central es que la subutilización de las capacidades de esta población está estrechamente vinculada con la migración a los Estados Unidos. Sobre la base de los datos de la Encuesta Nacional de Ocupación y Empleo (ENOE) de México y la American Community Survey (ACS) de los Estados Unidos (ambas de 2013) y a partir de una estrategia analítica que compara la situación laboral de esta población en México y en los Estados Unidos, los resultados muestran que los profesionales mexicanos de las áreas anteriormente citadas que se encuentran radicados en los Estados Unidos tienen una probabilidad mayor de participar en ocupaciones acordes con su formación . . .

The research project presented in this paper regards a joint cooperation between Medievalist Historians and Geomatics experts. The idea was to study if new tools based on Geomatics technologies could provide Historians with new methods to develop their studies, archiving digital data in a geo-database and “spatializing” the information sources to produce maps in a GIS environment. So, in the first part of the project, a GIS was designed and implemented based on data collected from documents preserved in the Italian National Archives. Afterwards, the problem of data integration and sharing among research groups working on Medieval History was dealt with, in order to make data available for the consultation and query by several research groups. Three approaches based on a client-server architecture have been explored: one is typical of the WebGIS architecture; the second one is based on OGC Web services and the third one exploits a Web page while the GIS tools are provided by a Desktop GIS installed locally on a PC. In the paper, the different approaches will be described, in order to underline advantages and disadvantages with respect to the Historians' requirements.

We study whether war service by one generation affects service by the next generation in later wars, in the context of the major U.S. theaters of the 20th century. To identify a causal effect, we exploit the fact that general suitability for service implies that the closer to age 21 an individuals father happened to be at a time of war is a key determinant of the fathers likelihood of participation. We find that a fathers war service has a positive and significant effect on his sons likelihood of service in the next generations war. Across all wars, we estimate an intergenerational transmission parameter of approximately 0.1. Quantitatively, our estimates imply that each individual war had a substantial impact on service in those that followed. This effect cannot be explained by broader occupational choice or labor market opportunity channels: fathers war service increases sons educational achievement and actually reduces the likelihood of military service outside of wartime. Instead, we find evidence consistent with cultural transmission from fathers to sons. Taken together, our results indicate that a history of wars helps countries overcome the collective action problem of getting citizens to volunteer for war service.

We present a methodology for estimating the distributional effects of an endogenous treatment that varries at the group level when there are group-level unobservable, a quantile extension of Hausman and Taylor (1981). Because of the presence of group-level unobservables, standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables. In contrast, our estimation technique is consistent as well as computationally simple, consisting of group-by-group quantile regression followed by two-stage least squares. Using the Bahadur representation of quantile estimators, we derive weak conditions on the growth of the number of observations per group-by-group are sufficient for consistency and asymptotic zero-mean normality of our estimator. As in Hausman and Taylor (1981), micro-level covariates can be used as internal instruments for the endogenous group-level treatment if they satisfy relevance and exogeneity conditions. An empirical application that low-wage earners in the US from 1990-2007 were significantly more affected by increased Chinese import competition than high-wage earners. Our approach applies to a broad range of settings in labor, industrial organization, trade, public finance, and other applied fields.

Demographic overview of Cambridge, Massachusetts prepared for the Community Engagement Team. Emphasis on characteristics of diverse populations and lower income population.

While it is difficult to gauge the effect of multicultural policies within countries, it is even more difficult to measure them across countries. In this article, I use fundamental multicultural changes that have occurred in Israeli society in recent decades as a case study, and track their effect on how Israelis who reside in the USA identify with Israel. Analysing the US census and the American Community Survey, I have focused my research on three groups of Israeli-born migrants in the USA Israeli Arabs, ultra-Orthodox Jews and the Jewish majority. Findings indicate that originating from a minority community in the homeland predicts not only a different rate, but also different longitudinal trends of Israeli identification. I offer several possible explanations for these variations, but an in-depth analysis of the Israeli case indicates that the transnational effect of the changing multicultural agenda in Israel is the leading mechanism at play.

This chapter begins with a short summary of how differentness evolved and how it has replaced expectations of sameness. The primary focus of the chapter is on looking ahead vis-a-vis differentness-where progress is lacking and areas to target for change. As will be seen, some of the prescriptions for change are not new and progress has been slow. For example, despite calls for greater diversity in the upper reaches of government at every level, sameness perdures. The field is also beginning to advance our knowledge into other realms of differentness, such as the employment of lesbians, gays, bisexuals, transgendered and questioning (LGBTQs). This issue will also be addressed. So, too, will be the issue of family responsibilities discrimination (FRD), or caregiver discrimination, which abrogates the rights of both women and men who are the primary caregivers for children, aging parents, or sick spouses or partners. Differentness is not simply a matter of change to the social composition of the workplace. Its importance also manifests in organizational cultures that support differences in choice, such as the ability of workers to make choices about parenting and caregiving.

Tras la debacle económico-financiera global de 2007-2008, con epicentro en Estados Unidos, creció el interés entre gobiernos nacionales, organismos internacionales y entidades académicas por conocer el impacto de este fenómeno en la población de migrantes en general y, específicamente, en la población de migrantes calificados. Diversos estudios han mostrado los efectos de esta crisis sobre la migración internacional: disminución del flujo de migrantes internacionales, aumento de las tasas de desempleo entre la población migrante, disminución de los flujos de remesas, aumento de la migración de retorno, entre otros aspectos (Skeldon, 2010; Castles y Miller, 2010; Papademetriou y Terrazas, 2009; Moser y Horn, 2013; MartínezPizarro, 2010). Sin bien estos efectos fueron más evidentes entre la población migrante de media y baja calificación —en particular aquella vinculada a sectores económicos como el de la construcción—, cabe preguntarse cómo afectó esta crisis a la población de . . .

Real local government spending in the United States has increased by 240% between 1972 and 2012, faster than can be explained by population growth (a 48% increase), growth in median household income (a 32% increase), or changes in other economic, demographic, and institutional variables typically used to explain the pattern in local government spending. In this paper we examine the role of other potential drivers of local government growth such as growing income disparity, the increasing number of single female-headed households, increasing number of household living in mobile homes, rising healthcare costs, and diminishing health such as increasing in obesity (and associated physical health problems) as well behavioral problems such as hyperactivity, anxiety, depression, and violence associated with the changing diet of the American people. Since the 1970s, the obesity rate in the United States has increased from 12% to 35%. Using the obesity rate as a proxy for changing health, we find that increasing mental/emotional/physical health problems accounts for a significant portion of increased local government spending growth, particularly in human services such as education that require behavioral management. We also find that as local government spending in other spending categories decline with obesity. These findings suggest that deteriorating mental/ emotional/physical health resulting from dietary changes and other factors has increased local government spending and shifted spending priorities.

Faced with an unprecedented drought, California has spent over half a billion dollars in cash rebates for home owners to tear out their lawns the largest outdoor conservation program in American history. Yet this programs impact and the path to turf market transformation remain unclear. Household water usage ranges from a mean of 417 to maximum of 17,817 gallons per day, and we highlight the need to move beyond one-size-fits-all conservation estimates. Using a synthesis of exploratory statistical analyses and robust models, we provide a structured, quantitative framework for water managers to think through substantial water usage variation and complex factors, both hydrological and behavioral, affecting the impact of turf rebates. These results are followed by a discussion of future water conservation impact evaluation opportunities vis a vis an unprecedented inter-utility, account-level water usage data collaborative currently being built by the authors in partnership with a key California.

Sociological research on high school dropouts is largely concerned with who drops out of school and why. Research on the consequences of dropping out is less common. There are clear theoretical reasons to expect dropping out to have a direct and negative effect on life outcomes; however, empirically evaluating these theories is difficult because students who drop out are different from high school graduates in meaningful and complex ways. In this article, I first provide a brief review of sociological research on high school dropouts, emphasizing the demographics of dropouts and reasons for dropping out. I then discuss the possible role of human capital differences, signaling theory, and social closure in creating worse outcomes for high school dropouts and outline the empirical challenges to researching the effects of dropping out. I conclude by discussing avenues for future research and important unanswered questions about the consequences of dropping out.

In the extensive literature on temperature and crime, a clear positive correlation between observed temperature and criminal activity has been documented. The dominant explanation for this effect is that observed temperature conditions affect planning, which leads to changes in the number of opportunities for crime. Since planning necessarily applies to activities occurring in the future, it is more accurate to say that the plans one makes depend on temperature expectations, both in the current period and the near future. In this paper, I examine the impact of temperature expectations on daily violent crime and property theft levels for a set of 50 U.S. cities during the 2004-2012 period. I find that the effect of observed maximum temperature on a given day is largely captured by temperature expectations for that day. However, I also find that crime is affected by expectations about weather in the near future, and that forecast errors (i.e. unexpectedly hot or cold temperatures) significantly impact violent crime (but not property theft). This set of findings represents an important contribution to the temperature-crime literature, and provides new insight into the determinants of criminal labor supply. Furthermore, these results have significant policy implications for short-run crime forecasting.

It is well known that family socioeconomic background influences childhood access to opportunities. Educational reforms that introduce new information about school quality may lead to increased inequality if families with more resources are better able to respond. However, these policies can also level the playing field for choice by equalizing disadvantaged families access to information. This study assesses how a novel accountability system affected family enrollment decisions in the Chicago Public Schools by introducing new test performance information and consequences. We show that a substantial proportion of families responded by transferring out when their childs school was assigned probation. Poor families transferred children to other schools in the district, but at a lower rate than non-poor families, who were also more likely to leave for another district or enroll in private school. Most striking, we show that despite family response to the probation label, access to higher-performing schools changed very little under the new policy; students who left probation schools were the most likely of all transfer students to enroll in other low-performing schools in the district. Although new information changed families behavior, it did not address contextual and resource-dependent factors that constrain the educational decisions of poor families.

Womens contributions to family income are essential for most families. This is obviously true for the growing number of single-mother families, but increasingly so for married couple families. While dual-earner families are doing relatively well, family income overall has been stagnant or decreasing among single-earner families, resulting in a widening income gap. This study provides an examination of married and single womens contributions to family income. Single women are comprised of those who are cohabiting, in same sex marriages, living alone, with parents or other family members, or living with roommates. In this brief, we consider family income for all single and married women. In the case that single women live alone or with nonrelatives, family income is comprised of the womans income. Analysis of Current Population Survey data for 2000 and 2013 shows that dual-earner couples have higher family incomes than sole-earner married couples or single women with or without children. Of different family types, married couples in which the husband is the primary earner (the husband earns 60 percent or more of total family earnings) had the highest median family income in 2013 ($101,000), followed closely by married couples in which both spouses had similar earnings ($98,000). In contrast, single mothers with children had the lowest median family income ($30,000). In addition, family income rose among dual-earner couples primarily due to an increase in these wives earnings, but declined among sole-earner married-couple and single-women families from 2000 to 2013, contributing to increased inequality. See Box 1 on page 2 for a definition of terms. Wives in husband primary-earner families consistently contributed 24 percent of family income, while wives in wife primary-earner families contributed 67 percent of family income in 2013.

Scientists, Technology professionals, Engineers, and Mathematicians - STEM workers or scientists and engineers for brevity - are the drivers of scientific and technological innovation and adoption. Several studies (e.g. Rauch, 1993; Iranzo and Peri, 2009) have emphasized the importance of a concentration of college- educated workers in enhancing local productivity. An agglomeration of scientists and engineers generates agglomerations of productive industries (Ellison and Glaeser, 1999) that, in turn, create local externalities and virtuous cycles of innovation (Jaffe et al., 1993; Saxenian, 2002). The presence of STEM workers in a local economy, such as a city, has been considered a main driver of productivity growth and economic success.

This chapter provides an analysis of the Chinese General Social Surveys of 2005 and 2010 with a focus on “felt-suffering” as measured by poor health, physical suffering, and mental suffering. All three of these measures increased from 2005 to 2010. During the 5-year span, worsening living conditions for older people, lower-status people, and those who lived in less-developed regions were the main factors for the increase in poor health. Enlarged socioeconomic inequalities were the leading cause to the increase in physical and mental suffering. The effects of gender, education, and social disconnection on felt-suffering were persistently strong in both 2005 and 2010.

Making scientific data openly accessible and available for re-use is desirable to encourage validation of research results and/or economic development. Understanding what users may, or may not, do with data in online data repositories is key to maximizing the benefits of scientific data re-use. Many online repositories that allow access to scientific data indicate that data is open, yet specific usage conditions reviewed on 40 open sites suggest that there is no agreed upon understanding of what open means with respect to data. This inconsistency can be an impediment to data re-use by researchers and the public.

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across the two classes. Several coupled systems at diverse scales in science, such as plant/pollinator in ecological networks or drug/target in molecular interactomes, can be approximated using bipartite network topology. Bipartite graphs emerge naturally also in many applicative domains. For instance, modelling the connections between workers and their employers, or electors and parties they vote for, are examples of affiliation networks in social analysis. Ultimately, predicting interactions between products and consumers in personal recommendation systems and market models can provide priceless information for managing cybercommerce. Surprisingly, current complex network theory presents a theoretical bottleneck: a general framework for local-based link prediction directly in the bipartite domain is missing1. Indeed, local state-of-the-art methods for link prediction do not directly exploit the inner bipartite topology2,3, but rather rely on its projection into two one-modedimension networks, an example of which is the monopartite network of consumers connected by products and the monopartite network of products connected by consumers. Unfortunately, the one-mode-projections are always less informative than the original bipartite structure4 . Here, we overcome this theoretical obstacle, and we present a formal definition of common neighbour index5 (CN) and local-community-paradigm6 (LCP) for bipartite networks. As a consequence, we are able to introduce the first nodeneighbourhood-based and LCP-based models for topological link prediction that utilizes the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks, and represent the first attempt to create a local-based formalism that allows to intuitively implement link prediction fully in the bipartite domain.