A Child Labour Estimator: A Case of Bahawalpur Division

Social Indicators Research - Child labor is a distressing issue. There have been many attempts to estimate its magnitude. It is attempted here to develop an estimator to assess the magnitude of...     

Prediction and Impact of Sea Level Rise on Properties and Infrastructure of Washington,DC

The city of Washington, District of Columbia (DC) will face flooding, and eventual geographic changes, in both the short‐ and long‐term future because of sea level rise (SLR) brought on by climate change, including global warming. To fully assess the potential damage, a linear model was developed to predict SLR in Washington, DC, and its results compared to other nonlinear model results. Using geographic information systems (GIS) and graphical visualization, analytical models were created for the city and its underlying infrastructure. Values of SLR used in the assessments were 0.1 m for the year 2043 and 0.4 m for the year 2150 to model short‐term SLR; 1.0 m, 2.5 m, and 5.0 m were used for long‐term SLR. All necessary data layers were obtained from free data banks from the U.S. Geological Survey and Washington, DC government websites. Using GIS software, inventories of the possibly affected infrastructure were made at different SLR. Results of the analysis show that low SLR would lead to a minimal loss of city area. Damages to the local properties, however, are estimated at an assessment value of at least US$2 billion based on only the direct losses of properties listed in real estate databases, without accounting for infrastructure damages that include military installations, residential areas, governmental property, and cultural institutions. The projected value of lost property is in excess of US$24.6 billion at 5.0 m SLR.     

AIDE: Adaptive intrapatient dose escalation designs to accelerate Phase I clinical trials

Designing Phase I clinical trials is challenging when accrual is slow or sample size is limited. The corresponding key question is: how to efficiently and reliably identify the maximum tolerated dose (MTD) using a sample size as small as possible? We propose model-assisted and model-based designs with adaptive intrapatient dose escalation (AIDE) to address this challenge. AIDE is adaptive in that the decision of conducting intrapatient dose escalation depends on both the patient's individual safety data, as well as other enrolled patient's safety data. When both data indicate reasonable safety, a patient may perform intrapatient dose escalation, generating toxicity data at more than one dose. This strategy not only provides patients the opportunity to receive higher potentially more effective doses, but also enables efficient statistical learning of the dose-toxicity profile of the treatment, which dramatically reduces the required sample size. Simulation studies show that the proposed designs are safe, robust, and efficient to identify the MTD with a sample size that is substantially smaller than conventional interpatient dose escalation designs. Practical considerations are provided and R code for implementing AIDE is available upon request.     

Consequences of Population Change for Retail/Wholesale Sector Employment in the Nonmetropolitan Great Plains: 1950–19961

Abstract A rural economic restructuring perspective and central place theory are used to assess the impact of population change on retail/wholesale sector employment for the 438 nonmetropolitan counties of the Great Plains region from 1950 to 1990. Findings indicate that county level population declined for every decade except the 1970 turnaround decade, and the greatest losses were in completely rural nonadjacent counties. The civilian labor force declined for all but the 1970 decade, when there was a substantial increase due to increased nonmetro manufacturing and the baby boom cohorts reaching labor force age. Retail/wholesale labor force increased in every decade except the 1980s. However, regression analysis found a positive and highly significant relationship between population change and retail/wholesale employment change. For this region, population decline is a major contributor to decline in the retail/wholesale employment sector at the county level. Preliminary data from the 1990–1996 period indicate a population and labor force rebound from the 1980s. However, as in the 1980s, gains are most likely concentrated in a small number of mainly urban nonadjacent counties.     

Internal and external evaluation of social work

In the UK a number of factors are bringing the idea of evaluation of social work into a new prominence. This paper considers the different meanings which may be attached to the terms internal and external in the context of social work evaluation, and outlines the differences between scientific, developmental and managerial approaches. It is argued that while some suspicion of the purpose of current demands for evaluation may be justified, the calls for greater accountability have some justice and are unlikely to diminish. If the domination of bureaucratic and financial considerations over professional judgements is to be avoided, social workers must overcome their alleged anti-evaluative professional culture and consider how to systematically evaluate their own practice, both individually and collectively.     

Inference of R=P[X<Y] for generalized logistic distribution

This paper deals with the estimation of R=P[X<Y] when X and Y come from two independent generalized logistic distributions with different parameters. The maximum-likelihood estimator (MLE) and its asymptotic distribution are proposed. The asymptotic distribution is used to construct an asymptotic confidence interval of R. Assuming that the common scale parameter is known, the MLE, uniformly minimum variance unbiased estimator, Bayes estimation and confidence interval of R are obtained. The MLE of R, asymptotic distribution of R in the general case, is also discussed. Monte Carlo simulations are performed to compare the different proposed methods. Analysis of a real data set has also been presented for illustrative purposes.     

Lebanon's economic reconstruction after the war: A bridge too far?

Since the onset of the Civil War in 1975 Lebanon has experienced burgeoning fiscal deficits and an unsustainable public debt overhang. Much of this arose from the loss of revenues during the period of the Civil War 1975–1990 and attempts to maintain basic public expenditure, while from 1990 to 2006 this reflected post-Taif rebuilding and reconstruction of key infrastructure with limited revenue capacity. Considerable progress from the 1990s had been achieved in rebuilding the shattered economy from both public and private international and domestic sources, but its legacy is a huge public debt and a servicing requirement that currently absorbs alone almost 30 per cent of total government revenue and is the highest in the world on a per capita basis. While the need to reduce this debt to a sustainable level would be daunting enough in itself, Lebanon's fiscal predicament was further compounded by the outbreak of war with Israel during July–August 2006. The consequence of this 34-day war was the devastation of residential property, vital infrastructure, loss of agricultural production, industrial production, exports, environmental damage, the collapse of tourism and a further erosion of the influence and power of the central government. Estimates of the direct and indirect costs for Lebanon of this relatively brief but devastating war conservatively vary from US$ 10–15 billion. The implications of such reconstruction and rebuilding costs for the budget and public debt are potentially calamitous for Lebanon which is already struggling under the weight of debt overhang and its servicing. A key question is whether Lebanon can tackle this enormous task in insolation.This paper explores the background to the fiscal crisis, identifies from available literature the extent, nature and cost of the war damage, analyses the options available to the authorities in rebuilding the economy and highlights key policy issues and measures that will be required if a sustainable economic recovery is to be achieved. Despite its demonstrated and remarkable resilience to past trauma the paper concludes that the fiscal crisis makes it impossible for Lebanon to tackle the reconstruction and rebuilding task on its own and particularly in the wake of the events of summer 2006. The country will require substantial and ongoing financial support from international lenders and donors. The success of these efforts in the case of Lebanon is of particular interest as it could well be a microcosm of possible future outcomes for the region more generally.     

Inference of stress-strength for the Type-II generalized logistic distribution under progressively Type-II censored samples

This article studies the estimation of the reliability R = P[Y < X] when X and Y come from two independent generalized logistic distributions of Type-II with different parameters, based on progressively Type-II censored samples. When the common scale parameter is unknown, the maximum likelihood estimator and its asymptotic distribution are proposed. The asymptotic distribution is used to construct an asymptotic confidence interval of R. Bayes estimator of R and the corresponding credible interval using the Gibbs sampling technique have been proposed too. Assuming that the common scale parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator, Bayes estimation, and confidence interval of R are extracted. Monte Carlo simulations are performed to compare the different proposed methods. Analysis of a real dataset is given for illustrative purposes. Finally, methods are extended for proportional hazard rate models.     

Determinants of marital fertility in Pakistan: the impact of education,work and family planning

The relative impact of the indirect and direct determinants of fertility of Pakistani women was assessed using the 1990/91 Pakistan Demographic and Health Survey (PDHS). A total of 7926 households was selected and 5713 women of reproductive age (15-49 years old) who had at least one birth were interviewed. Several social, economic, and demographic variables were employed to assess the number of children ever born. Ordinary least squares regression was used to estimate four multivariate models of children ever born. The direct and indirect determinants and the control variable of current age were simultaneously entered for each of four models that differed by age: 15-49, 15-24, 25-34, and 35-49 years. There was a 0.5 child difference between children ever born (4.64) and living children (4.11) for the 15-49 age group. This indicates infant and child mortality: 26% of the women experienced at least one child death before the age of 2 years. The oldest group had the lowest percentage ever attending school: 19% vs. 25% and 26% (15-24 and 25-34 age groups, respectively). Education was nonsignificant for the youngest and middle-aged cohorts, but it was negative and significant for the older cohorts. For employment, only the 25-34 age group was negative and significant. Age at marriage and breast feeding were strong and negative for all models. Current use of family planning was positive and significant for the oldest age group and the total. The younger cohorts did not have a negative and significant relationship between education and fertility; and the 15-24 age group living in a major city had significantly higher fertility than their town and village counterparts. The variables that showed differential impact were education, employment, residence, and contraceptive use. Education did not significantly lower fertility for the younger groups, but it did for the older group. Employment significantly lowered fertility for the 25-34 age group. Contraceptive prevalence steadily increased from 7% in the 15-19 age group to nearly 21% in the 35-39 age group.     

On the online multi-agent O–D <Emphasis Type="Italic">k</Emphasis>-Canadian Traveler Problem

In this article, we present new results on the online multi-agent O–D k-Canadian Traveler Problem, in which there are multiple agents and an input graph with a given source node O and a destination node D together with edge costs such that at most k edges are blocked. The blocked edges are not known a priori and are not recoverable. All of the agents are initially located at O. The objective is to find an online strategy such that at least one of the agents finds a route from the initial location O to a given destination D with minimum total cost. We focus on the case where communication among the agents is limited in the sense that some travelers can both send and receive information while the others can only receive information. We formalize the definition of agents’ intelligence by specifying three levels. We introduce two online strategies which utilize higher levels of agents’ intelligence to provide updated lower bounds to this problem. We show that one of our strategies is optimal in both cases with complete and limited communication in the special case of O–D edge-disjoint graphs and highest level of agents’ intelligence.