The Limits of Black Politics in the Post–Civil Rights Era

Pluralist theorists have long contended that to exercise power and influence in the American political system, blacks should come together like any other organized interest group, form coalitions with other like-minded people (white liberals), and advocate for policy reforms. Beginning during the “Black Power” era, the goal of putting black faces in high places to help address black concerns became a driving force in black politics. The deteriorating social and economic status of many in the black community, however, has not been prevented by either the political incorporation of more than 11,000 black elected officials or even the election of the nation’s first black president. This article will show how the inherent limitations of the pluralist interest-group strategy and a growing white backlash fueled by an awareness of changing demographics in the country has spawned an economic and political crisis in black America.     

Impact of Water Level Rise on Urban Infrastructures: Washington,DC, and Shanghai as Case Studies

The observed global sea level rise owing to climate change, coupled with the potential increase in extreme storms, requires a reexamination of existing infrastructural planning, construction, and management practices. Storm surge shows the effects of rising sea levels. The recent super storms that hit the United States (e.g., Hurricane Katrina in 2005, Sandy in 2012, Harvey and Maria in 2017) and China (e.g., Typhoon Haiyan in 2010) inflicted serious loss of life and property. Water level rise (WLR) of local coastal areas is a combination of sea level rise, storm surge, precipitation, and local land subsidence. Quantitative assessments of the impact of WLR include scenario identification, consequence assessment, vulnerability and flooding assessment, and risk management using inventory of assets from coastal areas, particularly population centers, to manage flooding risk and to enhance infrastructure resilience of coastal cities. This article discusses the impact of WLR on urban infrastructures with case studies of Washington, DC, and Shanghai. Based on the flooding risk analysis under possible scenarios, the property loss for Washington, DC, was evaluated, and the impact on the metro system of Shanghai was examined.     

Assessing reporting patterns of child sexual abuse within the Catholic Church using discontinuities in model parameter timeseries

Prior to 2002, little was known about sexual abuse within the Catholic Church. After the Boston Globe broke the story about John Geoghan - a priest in the Boston Archdiocese who was accused of abusing numerous children, convicted of one count of indecent assault, and eventually murdered in prison - the Church had many questions to answer. To this end, the United States Conference of Catholic Bishops (USCCB) commissioned John Jay College of Criminal Justice to research the nature and scope, as well as the causes and context of child sexual abuse within the Catholic Church.This research analyzes the data from the John Jay studies using a new quantitative technique, capable of adjusting for distortions introduced by delays in abuse reporting. By isolating discontinuities in model parameter timeseries, we determine changes in reporting patterns occurred during the period 1982-1988. A posteriori to the analysis, we provide some possible explanations for the changes in abuse reporting associated with the change-point. While the scope of this paper is limited to presenting a new methodological approach within the frame of a particular case study, the techniques are more broadly applicable in settings where reporting lag is manifested.     

Terrorist Population Dynamics Model

A system that includes a number of terrorist cells is considered. The cells can consist of one or more terrorists. The current number of terrorist cells is further denoted by N(t), where t is a current time counted from any appropriate origin. The objective is to find the evolution of the system in terms of N(t) and some interpretable parameters, such as the initial number of the terrorist cells N0=N(0), the cell disabling rate constant lambda (or the cell half-life t1/2), and the rate of formation of new cells P. The cost-effectiveness analysis, performed in the framework of the model, reveals that the effectiveness of disabling a terrorist cell is getting worse after 2-3 half-lives of a cell, which shows that if the anti-terrorist actions have not reached their goal during that time, the respective policy should be considered for revision, using the risk assessment consideration. Another important issue raised concerns balancing the efforts related to counterterrorism actions inside the system and the efforts protecting its borders. The respective data analysis is suggested and illustrated using simulated data.     

On the Bayes estimators of the parameters of size-biased generalized power series distributions

ABSTRACT

In this paper, we derive the Bayes estimators of functions of parameters of the size-biased generalized power series distribution under squared error loss function and weighted square error loss function. The results of size-biased GPSD are then used to obtain particular cases of the size-biased negative binomial, size-biased logarithmic series, and size-biased Poisson distributions. These estimators are better than the classical minimum variance unbiased estimators in the sense that they increase the range of the estimation. Finally, an example is provided to illustrate the results and a goodness of fit test is done using the maximum likelihood and Bayes estimators.     

Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the availability of H&S incident data, utilizing them to mitigate accident occurrence effectively is challenging due to inherent limitations of existing data logging methods. In this study, we used a text-mining approach for retrieving meaningful terms from data and develop six deep learning (DL) models for H&S risks management in power infrastructure. The DL models include DNN_classify (risk or no risk), DNN_reg1 (loss time), DNN_reg2 (body injury), DNN_reg3 (plant and fleet), DNN_reg4 (equipment), and DNN_reg5 (environment). An H&S risk database obtained from a leading UK power infrastructure construction company was used in developing the models using the H2O framework of the R language. Performances of DL models were assessed and benchmarked with existing models using test data and appropriate performance metrics. The overall accuracy of the classification model was 0.93. The average R² value for the five regression models was 0.92, with mean absolute error between 0.91 and 0.94. The presented results, in addition to the developed user-interface module, will help practitioners obtain a better understanding of H&S challenges, minimize project costs (such as third-party insurance and equipment repairs), and offer effective strategies to mitigate H&S risk.     

A Multifaceted Intervention with Savings Incentives to Reduce Multidimensional Child Poverty: Evidence from the Bridges Study (2012–2018) in Rural Uganda

Social Indicators Research - Using a randomized controlled trial design, we examine the effects of savings incentives (match rate 1:1 versus 1:2) with mentorship and financial trainings on child...     

Changes in the association between social housing tenure and child outcomes across cohorts: comparing the millennium and British cohort studies

ABSTRACT

In recent decades, social housing in the UK has increasingly become the preserve of the poorest in society. This paper is the first to investigate how the child outcome penalties associated with social housing tenure have changed over time across UK cohorts. I compare the differences in the cognitive, mental health, and physical health outcomes of children in social housing with children in non-social housing and evaluate whether these tenure differences have changed between the 1970 British Cohort Study (BCS) and the 2000 Millennium Cohort Study (MCS). I find that in both cohorts, children in social housing exhibit worse outcomes across all three dimensions (cognitive, mental health, and physical health) than children in non-social housing. For cognitive and physical health outcomes, however, the tenure difference has narrowed between the two cohorts, while for mental health outcomes, the tenure difference has widened. These results suggest that children have experienced a relative worsening in their mental health outcomes across cohorts, but also a relative improvement in both their cognitive and physical health outcomes. The findings suggest that policies aimed at reducing tenure inequalities in child outcomes should focus on mental health development in the early years.     

Migration,Diaspora and Citizenship: A Qualitative Study of the Perceptions of Pakistani Nationals towards the Political Rights of Pakistani Dual Citizens

The dual citizenship has been the subject of intense political debate in Pakistan barring the elected representatives, in parliament, the provincial assemblies and the presidency, from holding dual nationality. The perceptions that holding a foreign citizenship challenges the undiluted loyalty to country further engender question mark over their political participation in country’s affairs. A qualitative study has been carried out in the city of Rawalpindi to explore the stance of Pakistani nationals on such exclusion of Pakistani dual citizens from mainstream politics of Pakistan asking should the individual’s association to the state be an exclusive one? In this paper, in‐depth interviews were conducted with a sample of 40 male and female respondents (22 Pakistani citizens, 18 Pakistani dual citizens) and 6 constitutional experts. The results indicate distrust among Pakistani citizens when considering dual citizens’ right of representation in general elections of Pakistan, stemming from a mistrust of their “split loyalties”.