Risk Mapping of Groundwater‐Drawdown‐Induced Land Subsidence in Heterogeneous Soils on Large Areas

Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large‐scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics‐based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low‐risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk‐reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm.     

Affirming, Transforming, or Neglecting Gender? Conceptualizing Gender in the Pension Reform Process

This article analyzes the gender visions adopted by policy actorsin pension reform debates. Based on the work of Fraser (Fraser, N. 1994."After the Family Wage: Gender Equity and the Welfare State."Political Theory 22 : 591–618; Fraser, N. 1995. "FromRedistribution to Recognition? Dilemmas of Justice in a ‘Post-Socialist’Age." New Left Review 212:68–93), four gendered visionsof public pensions are introduced and then applied to pensionreforms in Belgium and Sweden. In line with international trends,both cases seek to integrate women within a pension system thattreats men and women the same regardless of their nonmarketactivities. However, in both cases, some compensation is introducedto acknowledge the caring functions performed mainly by women.Based on Fraser's typology, this arrangement leads to one ofthe worst-case scenarios since it legitimizes pension systemsthat are predominantly geared toward full-time contributorsand penalizes those individuals most likely to spend sometimesaway from the labor market. The Belgian case emphasizes thenegative role of the EU in retrenching pension rights and benefitsfor women. The Swedish case is interesting because of the scopeof its reform and the fact that women in the service sectorend up supporting the principle of tying benefits to contributions.     

Infant Sex Moderates the Effects of Maternal Pre‐ and Postnatal Stress on Executive Functioning at 8 Months of Age

Previous studies report that early life stress, including maternal pre‐ and postnatal stress, has adverse effects on cognitive development and that these associations might be sex‐specific. However, no studies exist on early life stress and infant executive functioning (EF). The aim of this study was to examine the relationship between maternal pre‐ and postnatal stress and infant EF, and whether these associations are moderated by infant sex. Maternal prenatal depressive, general anxiety, and pregnancy‐specific anxiety symptoms were measured three times, and postnatal depressive and general anxiety symptoms were measured 6 months postpartum. Infant EF was assessed with a modified A‐not‐B task 8 months postpartum (N = 214). Maternal postnatal general anxiety predicted poorer EF in girls in comparison with boys. Moreover, there was a trend toward an interaction between prenatal anxiety and infant sex such that prenatal anxiety predicted infant EF differently in girls and in boys. No association was found between depressive symptoms or pregnancy‐specific anxiety symptoms and infant EF. These findings suggest that maternal anxiety may have sex‐specific effects on early EF and that pre‐ and postnatal stress may differently affect infant EF/cognitive development. The implications of these findings and important future directions are discussed.     

Making Sense of After‐School Care Dilemmas in Mothers' Stories of After‐School Care in Finland and Sweden

The study focuses on dilemmas in storied experiences of everyday after‐school care arrangements among Swedish and Finnish mothers. Finland and Sweden, which share a history of strong labour market attachment among women, arrange institutional after‐school care in similar ways. The data consist of interviews with three Swedish and six Finnish mothers. A positioning analysis of four stories shows how decisions related to children's after‐school hours were allocated among different actors. Two reoccurring dilemmas, Competent‐dependent child stories and Unburdened‐deficient mother stories, emerged from the data analysis as related to prevailing moral discourses on childhood and motherhood.     

A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.     

Inferences concerning interpersonal choices given anonymously

It may be difficult or impossible to make a reliable empirical investigation of an unknown network of interpersonal choices or contacts if these are in some respect sensitive for the individuals involved. We consider how choice data given anonymously can be used to reveal various features of the network. Using tools from statistical decision theory and information theory we can determine risks and capacities of disclosing choice data, the graph structure of choice data and its numbers of loops and mutuals. We give some general results, illustrate the combinatorial complexity of the problem and comment upon the computational difficulties.