Leaving Science: Gender Differences in Career Continuity Following a Job Loss

This study investigates gender differences in the postdisplacement experience of nonacademic science and engineering (S&E) workers. Using a pooled sample created from the Displaced Worker Surveys conducted between 1994 and 2008, it finds that (1) this S&E work force is particularly vulnerable to job loss and potential career disruption; (2) displaced female S&E workers are more likely than comparable male workers to exit the work force, a gender difference that is conditional on and explained by marital and parental status; and (3) reemployed female S&E workers are also more likely to leave science for non‐S&E occupations, but this gender difference is limited to unmarried workers. A concluding section discusses the implications of these findings for interpreting gender differences in career outcomes.     

Continuing Care Retirement Communities:

No abstract available for this article.     

The persistence of white flight in middle-class suburbia

Scholars have continued to debate the extent to which white flight remains racially motivated or, in contrast, the result of socioeconomic concerns that proxy locations of minority residence. Using 1990–2010 census data, this study contributes to this debate by re-examining white flight in a sample of both poor and middle-class suburban neighborhoods. Findings fail to provide evidence in support of the racial proxy hypothesis. To the contrary, for neighborhoods with a larger non-white presence, white flight is instead more likely in middle-class as opposed to poorer neighborhoods. These results not only confirm the continued salience of race for white flight, but also suggest that racial white flight may be motivated to an even greater extent in middle-class, suburban neighborhoods. Theoretically, these findings point to the decoupling of economic and racial residential integration, as white flight may persist for groups even despite higher levels of socioeconomic attainment.     

Women's work in UK official statistics and the 1980 reclassification of occupations

Analyses using either time series or longitudinal data can be complicated by having to disentangle real changes from the artefactual effects imposed by the reclassification of key variables. In this paper the Warwick occupational conversion program is used to create adjustment tables which correct for the artefactual effect of the 1980 reclassification, along with coder errors, on 1971–1981 patterns of occupational sex segregation in longitudinal data from the Office for National Statistics's Longitudinal Study. The crowding of large numbers of women into a few occupational groups, which is consistent through the reclassification, arises in part because classification schemes fail to recognize the diversity in their work. This reflects past practice and the undervaluation of women's skills.     

Does race matter in the search for housing? An exploratory study of search strategies, experiences, and locations

In a departure from most studies of the causes of racial residential segregation that focus on the three main factors of economics, preferences, and discrimination, this paper examines one of the mechanisms through which segregation may be perpetuated: the housing search process itself. Data come from a 2004 face-to-face survey of an area probability sample of African American and white householders living in the three counties of the Detroit metropolitan area (n = 734). These data are used to address three research questions: (1) What are the strategies people use to find housing, and are there racial differences in those strategies? (2) Do whites and African Americans report similar or different experiences in the search for housing? (3) Do the locations in which people search for housing vary by race? Results show that once controlling for the type of search and background characteristics, the search strategies are generally similar for whites and blacks, though more so for buyers than renters: for example, black renters use more informal strategies and networks than do white renters. Analyses that look at the features of these strategies, however, reveal some significant racial differences. Search experiences are similar in terms of length and number of homes inspected, but other objective and subjective questions about the search show blacks at a disadvantage compared to whites: African Americans submit more offers/applications for homes, report more difficulties, and are much more likely to feel they were taken advantage of during the search. The racial characteristics of the communities in which blacks and whites search are quite different: whites mainly search in white communities, while African Americans search in communities with a variety of racial compositions. The paper concludes with a call for further research on housing search strategies, with particular attention to the role of social networks.     

Assessing the bias due to non-coverage of residential movers in the German Microcensus Panel: an evaluation using data from the Socio-Economic Panel

The German Microcensus (MC) is a large scale rotating panel survey over three years. The MC is attractive for longitudinal analysis over the entire participation duration because of the mandatory participation and the very high case numbers (about 200000 respondents). However, as a consequence of the area sampling that is used for the MC, residential mobility is not covered and consequently statistical information at the new residence is lacking in the MC sample. This raises the question whether longitudinal analyses, like transitions between labour market states, are biased and how different methods perform that promise to reduce such a bias. Similar problems occur also for other national Labour Force Surveys (LFS) which are rotating panels and do not cover residential mobility, see Clarke and Tate (2002). Based on data of the German Socio-Economic Panel (SOEP), which covers residential mobility, we analysed the effects of missing data of residential movers by the estimation of labour force flows. By comparing the results from the complete SOEP sample and the results from the SOEP, restricted to the non-movers, we concluded that the non-coverage of the residential movers can not be ignored in Rubin’s sense. With respect to correction methods we analysed weighting by inverse mobility scores and log-linear models for partially observed contingency tables. Our results indicate that weighting by inverse mobility scores reduces the bias to about 60% whereas the official longitudinal weights obtained by calibration result in a bias reduction of about 80%. The estimation of log-linear models for non-ignorable non-response leads to very unstable results.     

城市居住隔离的危害及出路探寻

居住隔离是我国城市居住空间在当前市场机制作用下的一种不可避免的现象。从居住隔离的概念、产生的原因、潜在的危害等方面展开了分析，提出防止居住隔离扩大化、构建和谐的居住空间的对策建议。     

A new family of random graphs for testing spatial segregation

The authors discuss a graph‐based approach for testing spatial point patterns. This approach falls under the category of data‐random graphs, which have been introduced and used for statistical pattern recognition in recent years. The authors address specifically the problem of testing complete spatial randomness against spatial patterns of segregation or association between two or more classes of points on the plane. To this end, they use a particular type of parameterized random digraph called a proximity catch digraph (PCD) which is based on relative positions of the data points from various classes. The statistic employed is the relative density of the PCD, which is a U‐statistic when scaled properly. The authors derive the limiting distribution of the relative density, using the standard asymptotic theory of U‐statistics. They evaluate the finite‐sample performance of their test statistic by Monte Carlo simulations and assess its asymptotic performance via Pitman's asymptotic efficiency, thereby yielding the optimal parameters for testing. They further stress that their methodology remains valid for data in higher dimensions.     

How much does income matter in neighborhood choice?

There is a substantial literature on the residential mobility process itself and a smaller contribution on how households make neighborhood choices, especially with respect to racial composition. We extend that literature by evaluating the role of income and socioeconomic status in the neighborhood choice process for minorities. We use individual household data from the Los Angeles Family and Neighborhood Study to investigate the comparative choices of white and Hispanic households in the Los Angeles metropolitan area. We show that income and education are important explanations for the likelihood of choosing neighborhoods. But at the same time, own race preferences clearly play a role. While whites with more income choose more white neighborhoods, Hispanics with more income choose less Hispanic neighborhoods. One interpretation is that both groups are translating resources, such as income and education, into residence in whiter and ostensibly, higher status neighborhoods.