Child Rights Practice among the Indigenous Communities in Bangladesh

The objective of this article was to explore the practice of child rights among the indigenous communities of Bangladesh. We used a mixed method approach to collect data from four ethnic communities in the Bandarban District of the Chittagong Division in Bangladesh. We questioned children, parents, community members, local leaders, and service providers of those communities on a number of child rights issues, for example, child education, child labor, child recreation and culture, parents' guidance to children for capacity development, and access to child rights at home and in the community according to Convention on the Rights of the Child treaty. The results showed that while the community was aware of child rights, financial vulnerability and a lack of social support meant that these rights could not be upheld in practice. The paper urges improvement of social support, including income generation activities for indigenous communities.     

Random effects models for operational patient pathways

Patient flow modeling is a growing field of interest in health services research. Several techniques have been applied to model movement of patients within and between health-care facilities. However, individual patient experience during the delivery of care has always been overlooked. In this work, a random effects model is introduced to patient flow modeling and applied to a London Hospital Neonatal unit data. In particular, a random effects multinomial logit model is used to capture individual patient trajectories in the process of care with patient frailties modeled as random effects. Intuitively, both operational and clinical patient flow are modeled, the former being physical and the latter latent. Two variants of the model are proposed, one based on mere patient pathways and the other based on patient characteristics. Our technique could identify interesting pathways such as those that result in high probability of death (survival), pathways incurring the least (highest) cost of care or pathways with the least (highest) length of stay. Patient-specific discharge probabilities from the health care system could also be predicted. These are of interest to health-care managers in planning the scarce resources needed to run health-care institutions.     

Learning organization and development of woman managers in Pakistan

Women's participation in economic activities in general and at managerial status in particular is insignificant in Pakistan. Furthermore, the opportunities for professional development of women managers are meagre because of multiple socio-cultural limitations. This paper attempts to draw a profile of female managers focusing, inter alia, on the trend and structure of women's human resource, ratio of employment, work environment and scope of development, efficiency at work, satisfaction level, professional commitment and forces inhibiting women access to jobs under the learning organization perspectives. It also exhibits issues bearing policy implications in regard to the development of women as managers and also as human resource.     

Statistical Analysis of Marginal Count Failure Data

Manufacturers want to assess the quality andreliability of their products. Specifically, they want to knowthe exact number of failures from the sales transacted duringa particular month. Information available today is sometimesincomplete as many companies analyze their failure data simplycomparing sales for a total month from a particular departmentwith the total number of claims registered for that given month.This information—called marginal count data—is, thus,incomplete as it does not give the exact number of failures ofthe specific products that were sold in a particular month. Inthis paper we discuss nonparametric estimation of the mean numbersof failures for repairable products and the failure probabilitiesfor nonrepairable products. We present a nonhomogeneous Poissonprocess model for repairable products and a multinomial modeland its Poisson approximation for nonrepairable products. A numericalexample is given and a simulation is carried out to evaluatethe proposed methods of estimating failure probabilities undera number of possible situations.     

A speciation-based bilevel niching method for multimodal truss design problems

Truss design is a well-known structural optimization problem that has important practical applications in various fields. Truss design problems are typically multimodal by nature, meaning that it offers multiple optimal solutions concerning the topology (combinatorial optimization problem) and/or sizes (continuous optimization problem) of the members, but they are evaluated to have similar or equally good objective function values. From a practical standpoint, it is desirable to find as many alternative designs as possible, rather than finding a single design, as often practiced. Several techniques based on classical and metaheuristic optimization methods have been developed for simultaneous optimization of topology and size of a truss. However, all these methods unable to find multiple topologies and their corresponding size solutions in a single run. A few metaheuristics incorporating niching techniques have been developed for finding multiple topologies for the truss design problem, but these studies ignored the fact that for each known topology, multiple design solutions in terms of size can be found. To address this issue, this paper proposes a bi-level truss formulation and subsequently a speciation-based bilevel niching method (BiL-NM) using such a formulation. The BiL-NM consists of a modified SPSO niching method which is robust to find multiple topologies and a canonical PSO for their corresponding size solutions. Extensive empirical studies are carried out to analyze the accuracy, robustness, and efficiency of the BiL-NM. The results confirm that the proposed BiL-NM is superior in all these three aspects over the state-of-the-art methods on several low to high-dimensional truss design problems.

     

Enrolling girls without learning: Evidence from public schools in Afghanistan

While more girls are now attending school in Afghanistan than prior to 2010, there is a lack of evidence on how school attendance is helping their cognitive development. We use data from a large sample of all‐girls state‐funded school students to estimate for the first time the “learning profile” for Afghanistan. Students enrolled in grades 4 to 9 were assessed using the Early Grade Reading Assessment (EGRA) and the Early Grade Mathematics Assessment (EGMA) test items. We find that higher grade progression (particularly in grades 6–9) leads to almost no gain in numeracy (addition and subtraction) skills that should have been achieved in early grades. Similar results follow from the analysis of student performance in the EGRA test, particularly in oral reading fluency (correct words read per minute) and oral reading comprehension (number of correct answers out of 12). These findings warn that simply enrolling girls in school without improving the relationship between grade completion and learning is unlikely to transform the lives of women in Afghanistan.     

The nexus between extreme weather events,sexual violence,and early marriage: a study of vulnerable populations in Bangladesh

Population and Environment - This study aims to explore whether a relationship exists between extreme weather events, sexual violence, and early marriage. We selected two districts in Bangladesh...     

Assessing recall bias and measurement error in high-frequency social data collection for human-environment research

Population and Environment - A major impediment to understanding human-environment interactions is that data on social systems are not collected in a way that is easily comparable to natural...     

Correction to: Assessing recall bias and measurement error in high-frequency social data collection for human-environment research

Population and Environment - The original version of this article unfortunately contained a mistake. The name of “Md. Ehsanul Haque Tamal” is now corrected in the author group of this...     

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.