Fear of Crime and Collective Action: An Analysis of Coping Strategies

Recent research addressing fear of crime largely concerns the causes of that fear; this article expands our understanding of fear of crime by examining whether people cope with their fear individually or collectively. Our guiding questions were two: Do coping strategies differ by those individual-level characteristics established in the fear-of-crime literature? And do strategies differ based upon conceptually distinct types of fear? This research, based on a 1995 telephone survey of a random sample of New Orleans residents, suggests that the answer to both questions is yes. Commodified, individual-level precautionary techniques are explained primarily by characteristics that reflect differential abilities to pay for such precautions. Conversely, collective-level coping strategies are predicted primarily by degree of affective fear based on emotional reactions, regardless of actual levels of victimization.     

Applications of bivariate and univariate local lyapunov exponents

Chaotic systems are characterized by sensitivity to initial conditions, and this property can be measured by global Lyapunov exponents, which are measures of the average divergence rate of initially close trajectories. Wolff (1992) introduced local Lyapunov exponents and used them to obtain two diagnostic plots for differentiating between stochastic and deterministic time series. We extend the definition of the local Lyapunov exponent and the diagnostic plots to accommodate time series that arise from bivariate maps and investigate the behaviour of the local Lyapunov exponents and the corresponding diagnostic plots for some dynamical systems and stochastic time series. We consider the application of these diagnostic plots to some heart rate variability data.     

Enhanced services and stipends for foster parents: effects on retention rates and outcomes for children.

Current national trends show that although the number of available foster homes is shrinking, the number of children and adolescents being cared for in the family foster care system is growing. This study demonstrates the significant benefits to both foster parents and the children in their care of providing enhanced services and stipends to foster parents.     

Employment Exits and the Race Gap in Young Women's Employment*

Objective. A race gap in employment that disadvantages young African‐American women has emerged for the first time in U.S. history. This article addresses the extent to which race differences in employment entry, exits, or both are responsible for the gap. Methods. The article relies on event‐history analysis using NLSY data. Results. Analyses show that differences in rates of exit, not entry, explain the race gap. Factors encouraging higher exit rates among African‐American than white women include lower AFQT scores and greater numbers of children. Conclusion. These findings raise questions about the utility of focusing on employment processes at the point of employment entry, at least for processes involving young women. The importance of exits in understanding race differences in women's employment calls attention to processes within firms that present barriers to African‐American women.     

SEMI-MECHANISTIC MODELLING IN NONLINEAR REGRESSION: A CASE STUDY

This paper discusses the use of highly parameterized semi‐mechanistic nonlinear models with particular reference to the PARJIB crop response model of Reid (2002) [Yield response to nutrient supply across a wide range of conditions 1. Model derivation. Field Crops Research 77, 161–171]. Compared to empirical linear approaches, such models promise improved generality of application but present considerable challenges for estimation. Some success has been achieved with a fitting approach that uses a Levenberg–Marquardt algorithm starting from initial values determined by a genetic algorithm. Attention must be paid, however, to correlations between parameter estimates and an approach is described to identify these based on large simulated datasets. This work illustrates the value for the scientist in exploring the correlation structure in mechanistic or semi‐mechanistic models. Such information might be used to reappraise the structure of the model itself, especially if the experimental evidence is not strong enough to allow estimation of a parameter free of assumptions about the values of others. Thus statistical modelling and analysis can complement mechanistic studies, making more explicit what is known and what is not known about the processes being modelled and guiding further research.     

The evolution of federal employment

The first federal employees (other than Founding Fathers) were clerks. As federal employment grew in the 1820s, its ranks came to be dominated by patronage workers. After the Civil War, bureaucrats slowly displaced patronage workers at the federal level. Now, federal employments are being privatized and the bureaucracy shrunk. I explain this evolution of federal employment with one simple model of politics in a changing environment. Politicians combine into political firms to promise benefits to subsets of voters in return for election. If elected, politicians provide the benefits as efficiently as possible. Thus, politicians choose the form and size of their political firms to maximize expected political profits. Environmental changes affect the choices. The breach of the Appalachians in the 1810s, defeat of the South in the Civil War and the simultaneous rise of big and transcontinental industry, and contemporary worldwide economic inte-gration (globalization) are three environmental changes that changed the efficient organization of federal political firms.     

INTEGRATING ECONOMIC DUALISM AND LABOR MARKET SEGMENTATION:

Although the U.S. economy of the early twenty-first century is vastly different from the U.S. economy prior to the 1970s, the nature of these economic changes and their impact on U.S. workers is unclear. This article claims that despite contemporary economic shifts, differential labor and employer power continues to segment the economy, and workers' position in the labor market continues to predict their rewards, beyond the effects of gender, race, and human capital. Drawing on segmented labor market and dual economy research, we propose a four-category model of the structural factors that influence variance in work-related rewards. We examine the distribution of jobs in each of four categories between 1974 and 2000 and observe that losses and gains across categories are unevenly distributed by race and gender. While white men have experienced the greatest declines in employment and earnings, they have maintained their absolute advantage over women and nonwhites. In multivariate analyses, we find that the structural position of employment continues to be a significant determinant of wages. Although women and racial minorities have experienced sizable increases in employment in primary labor market jobs in the core of the economy, both groups remain overrepresented in low-paying jobs. Moreover women, but not nonwhite men, consistently receive significantly fewer rewards for their labor in both low-paying and high-paying jobs. Our findings suggest that structural factors continue to influence earnings inequality, especially across race and gender lines.     

The effect of the sex composition of jobs on starting wages in an organization: Findings from the NLSY

We show that individuals in a job with a higher percentage of females earn lower starting wages with an employing organization. This holds true with controls for individuals’ human capital, job demands for skill or difficult working conditions, and detailed industry. We use a measure of sex composition that applies to detailed jobs: cells in a three-digit census occupation by three-digit census industry matrix. We use pooled panel data from the 19791987 waves of the National Longitudinal Survey of Youth. The unit of analysis is the spell-the time in which a person worked for one organization. The dependent variable is the first wage in the spell. We use models with fixed-effects to control for unmeasured, unchanging individual characteristics; we also show results from OLS and weighted models for comparison. The negative effect on wages of the percentage female in one’s job is robust across procedures for black women, white women, and white men. For black men the sign is always negative but the coefficient is often nonsignificant.