Amassing rural power in the fight against fracking in Maryland: A report from the field

ABSTRACT

Social workers can mobilize vulnerable populations to shape policy decisions about industrial practices that could have adverse impacts on their wellbeing. One such practice is hydraulic fracturing or “fracking” to extract oil and natural gas from shale rock deposits. There is scant social work literature on mobilizing opposition to fracking despite a proliferation of literature from other disciplines. This article documents the campaign in Maryland that led to the adoption of the first legislative ban on fracking in a U.S. state with shale gas reserves, using social movement theory to identify factors that led to this successful outcome.     

Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy

Abstract

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.     

Die Bedeutung der Zinsschranke

The German Corporate Tax Reform Act of 2008 requires an adjustment of classic valuation concepts because it limits interest deduction from taxable income depending on the operating performance of the company. By using time- and state-contingent discount rates in a risk-neutral valuation with predetermined debt levels, a theoretically sound valuation result is obtained. However, a modified APV-concept which assumes deterministic debt over the planning horizon and constant leverage in the terminal value phase also yields consistent valuation results when two types of tax shields with different levels of risk are distinguished.     

Cox regression with missing covariate data using a modified partial likelihood method

Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard function with the idea being to profile out this function before carrying out the estimation of the parameter of interest. In this step one uses a Breslow type estimator to estimate the cumulative baseline hazard function. We focus on the situation where the observed covariates are categorical which allows us to calculate estimators without having to assume anything about the distribution of the covariates. We show that the proposed estimator is consistent and asymptotically normal, and derive a consistent estimator of the variance–covariance matrix that does not involve any choice of a perturbation parameter. Moderate sample size performance of the estimators is investigated via simulation and by application to a real data example.     

On the robustness of the generalized fused lasso to prior specifications

Using networks as prior knowledge to guide model selection is a way to reach structured sparsity. In particular, the fused lasso that was originally designed to penalize differences of coefficients corresponding to successive features has been generalized to handle features whose effects are structured according to a given network. As any prior information, the network provided in the penalty may contain misleading edges that connect coefficients whose difference is not zero, and the extent to which the performance of the method depend on the suitability of the graph has never been clearly assessed. In this work we investigate the theoretical and empirical properties of the adaptive generalized fused lasso in the context of generalized linear models. In the fixed \(p\) setting, we show that, asymptotically, adding misleading edges in the graph does not prevent the adaptive generalized fused lasso from enjoying asymptotic oracle properties, while forgetting suitable edges can be more problematic. These theoretical results are complemented by an extensive simulation study that assesses the robustness of the adaptive generalized fused lasso against misspecification of the network as well as its applicability when theoretical coefficients are not exactly equal. Our contribution is also to evaluate the applicability of the generalized fused lasso for the joint modeling of multiple sparse regression functions. Illustrations are provided on two real data examples.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.     

Cell Phone Survey Feasibility in The U.S.: Sampling and Calling Cell Numbers Versus Landline Numbers

In 2004, we conducted a nationwide dual frame survey of landlineand cell phone numbers to evaluate the feasibility of includingcell phone numbers in a random digit dial telephone survey.Households with both landline and cell phones were eligiblefor selection in both samples. This article describes our designand data collection methods; compares the results from the twosamples (with an emphasis on operational characteristics); andpresents the outcomes of two experimental manipulations designedto improve the cell phone response rate.     

Intergenerational class mobility in contemporary Britain: political concerns and empirical findings

In Britain in recent years social mobility has become a topic of central political concern, primarily as a result of the effort made by New Labour to make equality of opportunity rather than equality of condition a focus of policy. Questions of the level, pattern and trend of mobility thus bear directly on the relevance of New Labour's policy analysis, and in turn are likely be crucial to the evaluation of its performance in government. However, politically motivated discussion of social mobility often reveals an inadequate grasp of both empirical and analytical issues. We provide new evidence relevant to the assessment of social mobility - in particular, intergenerational class mobility - in contemporary Britain through cross-cohort analyses based on the NCDS and BCS datasets which we can relate to earlier cross-sectional analyses based on the GHS. We find that, contrary to what seems now widely supposed, there is no evidence that absolute mobility rates are falling; but, for men, the balance of upward and downward movement is becoming less favourable. This is overwhelmingly the result of class structural change. Relative mobility rates, for both men and women, remain essentially constant, although there are possible indications of a declining propensity for long-range mobility. We conclude that under present day structural conditions there can be no return to the generally rising rates of upward mobility that characterized the middle decades of the twentieth century - unless this is achieved through changing relative rates in the direction of greater equality or, that is, of greater fluidity. But this would then produce rising rates of downward mobility to exactly the same extent - an outcome apparently unappreciated by, and unlikely to be congenial to, politicians preoccupied with winning the electoral 'middle ground'.