The Politics of Race and Gender: Children's Perceptions of Discrimination and the U.S. Presidency

In the year prior to Hillary Clinton's and Barack Obama's bids to become the Democratic nominee for the U.S. presidency, we explored children's views about the role of race and gender in the U.S. presidency, with a specific focus on perceptions of discrimination. Specifically, we examined children's (aged 5 to 10) knowledge of and attributions for the lack of female (Study 1, N = 76), African American (Study 2, N = 64), and Latino (Study 3, N = 65) presidents. Results indicated that children are knowledgeable about the gender, race, and ethnicity of past presidents, and that many children attribute the lack of female, African American, and Latino presidents to gender and racial discrimination. Theoretical and policy implications of the work are discussed.     

Creating High‐Technology Growth: High‐Tech Employment Growth in U.S. Metropolitan Areas, 1988–1998*

Objective. Growth in the share of high‐technology employment is critical to discussions of the postindustrial transition. Do new state and local technology policies create growth in the share of high‐technology employment? This article examines this question along with the effects of location and agglomeration advantages, identifying sources of qualitative growth in the U.S. economy. Methods. We examine change in the share of high‐technology employment in metropolitan statistical areas (MSAs) in the United States between 1988 and 1998. High‐technology employment is measured from the BLS Current Employment Statistics Survey. The scale of state and local technology policies are measured from a comprehensive survey of state and local technology programs. A generalized linear model (GLM) estimates the effects of technology policies along with regional proximity, location, and agglomeration factors. Results. Technology grant and loan programs and research parks have direct effects on the share of high‐technology employment, along with private venture capital firms and military R&D. Research parks also magnify the effects of private venture capital firms, while public venture programs and technology development policies compensate for agglomeration deficits. Rapid population growth provides a more conducive context for these policies but does not directly influence growth in the share of high‐technology jobs. Conclusion. State and local technology policies compensate for and magnify the effects of agglomeration advantages, indicating that state and local government can play a strategic role in high‐technology development.     

The use of an identity in Anderson for multivariate multiple testing

Consider the model where there are I$I$ independent multivariate normal treatment populations with p×1$p\times 1$ mean vectors _μi${\mathit{\mu }}_i$, i=1,…,I$i=1,\dots ,I$, and covariance matrix Σ$\Sigma$. Independently the (I+1)$(I+1)$st population corresponds to a control and it too is multivariate normal with mean vector _μI+1${\mathit{\mu }}_{I+1}$ and covariance matrix Σ$\Sigma$. Now consider the following two multiple testing problems.     

Parametric bootstrap goodness-of-fit testing for Wehrly–Johnson bivariate circular distributions

The Wehrly–Johnson family of bivariate circular distributions is by far the most general one currently available for modelling data on the torus. It allows complete freedom in the specification of the marginal circular densities as well as the binding circular density which regulates any dependence that might exist between them. We propose a parametric bootstrap approach for testing the goodness-of-fit of Wehrly–Johnson distributions when the forms of their marginal and binding densities are assumed known. The approach admits the use of any test for toroidal uniformity, and we consider versions of it incorporating three such tests. Simulation is used to illustrate the operating characteristics of the approach when the underlying distribution is assumed to be bivariate wrapped Cauchy. An analysis of wind direction data recorded at a Texan weather station illustrates the use of the proposed goodness-of-fit testing procedure.     

A comparison of soil carbon dynamics in residential yards with and without trees

Residential lawns provide chronosequences to examine influences of home age and aboveground tree biomass (ATB) on soil carbon (C) levels. Soil C dynamics were compared between 44 lawns with trees (LwT) and 23 without trees (PL). At the 0–15 cm depth, LwT had higher mean soil C than PL and an earlier rise in median soil C across home age. Nonparametric quantile regression also showed a steeper rise in the 5th, 50th, and 95th soil C quantiles for LwT. Fitted polynomial regression models indicated that home age and ATB together accounted for 40 % of the soil C variation at the 0–15 cm depth [C = 1.34 + 0.05(Age) + 0.0003(ATB)]. At the 15–30 cm depth, the interaction between home age and ATB explained 33 % of the soil C variation [C = 0.78 + 0.0003(Age*ATB)]; at 30–50 cm, ATB was responsible for 20 % [C = 0.56 + 0.0003(ATB)].     

The analysis of linkages in demographic theory

Many seemingly different questions that arise in the analysis of population change can be phrased as the same technical question: How, within a given demographic model, would variable y change if the age- or time-specific function f were to change arbitrarily in shape and intensity? At present demography lacks the machinery to answer this question in analytical and general form. This paper suggests a method based on modern functional calculus for deriving closed-form expressions for the sensitivity of demographic variables to changes in input functions or schedules. It uses this “linkage method” to obtain closed-form expressions for the response of the intrinsic growth rate, birth rate, and age composition of a stable population to arbitrary marginal changes in its age patterns of fertility and mortality. It uses it also to obtain expressions for the transient response of the age composition of a nonstable population to time-varying changes in the birth sequence, and to age-specific fertility and mortality patterns that change over time. The problem of “bias” in period vital rates is also looked at.     

The Ergodic Theorems of Demography: a Simple Proof

Standard proofs of the ergodic theorems of demography rely on theorems borrowed from positive matrix theory, tauberian theory, and the theory of time-inhomogeneous Markov matrices. These proofs are efficient and expedient, but they give little direct insight into the mechanism that causes ergodicity. This paper proposes a simple and unified proof of the two ergodic theorems. It is shown that the birth dynamics can be decomposed into a smoothing process that progressively levels out past fluctuations in the birth sequence and a reshaping process that accounts for current period-to-period changes in vital rates. The smoothing process, which causes the birth sequence to lose information on its past shape, is shown to be the ergodic mechanism behind both theorems.     

Some general relationships in population dynamics

This paper extends the Lotka system of stable population equations to any population. The authors present this new general system and describe its duality with the recent Preston-Coale system. They derive these results by considering the calculus of change on the surface of population density defined over age and time. They show that analysis of this Lexis surface leads to all the known fundamental relationships of the dynamics of single-region human populations, several interesting new relationships, and a duality between period and cohort life tables.     

Quantifying socio-environmental impacts of predator control policies

Quantitative indices of the socio-environmental impacts of predator control were derived from a mathematical synthesis of public perceptions and physical measures of environmental change. A nationwide survey of the U.S. public yielded cardinal measures of preference for the acceptability, primary and secondary effects on other wildlife, and cost effectiveness of control policies. To determine the public evaluation of a particular policy, the preference values were used to weight social indicators describing the physical impacts of a policy. Policymakers will be able to use the resulting values to view the tradeoffs between economic and socio-environmental costs and benefits of various policy alternatives.