Participatory child poverty assessment in rural Vietnam

There are increasing calls for more child specific measures of poverty in developing countries and the need for such measures to be multi‐dimensional (that is not just based on income) has been recognised. Participatory Poverty Assessments (PPAs) are now common in international development research. Most PPAs have been undertaken with adults and there are still relatively few PPAs with children. The objective of the current study was to understand adults' and children's perceptions of the causes and consequences of child poverty in rural Vietnam using a variety of participatory methods. Poor children are perceived by poor children as those who lack basic needs such as food, clothes, and safe shelter. Poor children feel they do not receive enough attention from their parents, have to work and have no safe place to play.     

Penalized spline joint models for longitudinal and time-to-event data

The joint models for longitudinal data and time-to-event data have recently received numerous attention in clinical and epidemiologic studies. Our interest is in modeling the relationship between event time outcomes and internal time-dependent covariates. In practice, the longitudinal responses often show non linear and fluctuated curves. Therefore, the main aim of this paper is to use penalized splines with a truncated polynomial basis to parameterize the non linear longitudinal process. Then, the linear mixed-effects model is applied to subject-specific curves and to control the smoothing. The association between the dropout process and longitudinal outcomes is modeled through a proportional hazard model. Two types of baseline risk functions are considered, namely a Gompertz distribution and a piecewise constant model. The resulting models are referred to as penalized spline joint models; an extension of the standard joint models. The expectation conditional maximization (ECM) algorithm is applied to estimate the parameters in the proposed models. To validate the proposed algorithm, extensive simulation studies were implemented followed by a case study. In summary, the penalized spline joint models provide a new approach for joint models that have improved the existing standard joint models.     

Treatment of Female Pathological Gambling: The Efficacy of a Cognitive-Behavioural Approach

Given that a substantial proportion of current pathological gamblers are female, it is evident that women are underrepresented in the treatment outcome literature. The current study was designed to redress the limited information on the treatment of female pathological gambling. Although the use of cognitive-behavioural therapy is the most highly recommended approach as ‘best practice’ for the treatment of pathological gambling, no attempt to date has been made to evaluate the efficacy of this approach for female pathological gambling. Nineteen female pathological gamblers with electronic gaming machine problems were treated with a cognitive-behavioural program. While pathological gamblers placed on a waiting list did not show significant improvement on gambling behaviour and psychological functioning measures, the female pathological gamblers showed significant improvement on these measures over the treatment period, and maintained this improvement at the 6-month follow-up evaluation. By the completion of the follow-up period, 89% of participants no longer met diagnostic criteria for pathological gambling. Although further scientific demonstration and replication are required, the outcomes of this study indicate that the therapy that is considered ‘best practice’ in the treatment of pathological gambling is effective for female pathological gambling.     

Muddiman E., Power S., Taylor C. Civil Society and the Family. Policy Press,Bristol, 2020, pp. 203, References,Index, £60.00. ISBN 978-1-4473-5552-6

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

RIVERINE CROSSINGS: GENDER,IDENTITY AND THE RECONSTRUCTION OF NATIONAL MYTHIC NARRATIVE IN THE CRYING GAME

The Crying Game's central, tragic theme of warrior/lovers caught between their love for one another and loyalty to their respective factions has significant roots in early Celtic mythology. The elegaic theme of potential lovers forced into ill-fated combat that frames the film's events also, significantly, bears the weight of the film's most unambiguous political commentary, when Fergus speaks directly to the picture of Jody in Dil's apartment, telling him: ‘You should have stayed at home.’ This sad remonstration, which clearly lays responsibility for the chain of causality that has led to so much suffering not with Jody, but with the British state, is similar in quality to Cu Chulainn's lament as he contemplates his meeting with Ferdia. When we listen carefully for ways in which Celtic mythical themes underlie and nuance the film's events, different rhythms emerge, accenting different beats.     

Improved estimators for the location of double exponential distribution

In this paper, attention is focused on estimation of the location parameter in the double exponential case using a weighted linear combination of the sample median and pairs of order statistics, with symmetric distance to both sides from the sample median. Minimizing with respect to weights and distances we get smaller asymptotic variance in the second order. If the number of pairs is taken as infinite and the distances as null we attain the least asymptotic variance in this class of estimators. The Pitman estimator is also noted. Similarly improved estimators are scanned over their probability of concentration to investigate its bound. Numerical comparison of the estimators is shown.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

The type I distribution of the ratio of independent “Weibullized” generalized beta-prime variables

In this paper we introduce the distribution of , with c >  0, where X _i , i =  1, 2, are independent generalized beta-prime-distributed random variables, and establish a closed form expression of its density. This distribution has as its limiting case the generalized beta type I distribution recently introduced by Nadarajah and Kotz (2004). Due to the presence of several parameters the density can take a wide variety of shapes.