Challenges of implementing restorative justice for intimate partner violence: An Islamic perspective

ABSTRACT

Intimate partner violence (IPV) is currently recognized as a critical public health concern and a human rights issue. Not surprisingly, Muslims – a religiously and socio-culturally diverse faith-based populace – are not an exception. To address this complex area of criminal justice and social policy, some scholars advocate implementing restorative justice (RJ) approaches. While RJ approaches have been traditionally used in Islamic cultures for conflict resolutions, to date, few studies have investigated how RJ operates in dealing with IPV in Muslim countries and communities. This article explores how RJ approaches towards IPV operate in some Muslim countries/communities, and offers insights into developing culturally and religiously appropriate ways of implementing RJ in IPV situations among Muslims. Given the prevalence of IPV among Muslims, the question is particularly important and timely. Taking exclusively limited examples of RJ approaches that have been used to mediate IPV cases in Muslim countries and communities, this paper found one significant challenge in the RJ approaches among Muslims: community acceptance of IPV. To reduce IPV in Muslim society, it is necessary to develop treatment models and techniques that meet cultural and religious needs. This paper found that since RJ is not alien to Islamic teachings, RJ approaches can be implemented effectively in dealing with IPV among Muslims by ensuring justice and equity of the abused woman. The findings of this paper will assist policymakers, practitioners, and service providers in providing religiously and culturally appropriate care when addressing IPV issues among Muslims.     

A robust sample spatial outlyingness function

Sample quantile, rank, and outlyingness functions play long-established roles in univariate exploratory data analysis. In recent years, various multivariate generalizations have been formulated, among which the “spatial” approach has become especially well developed, including fully affine equivariant/invariant versions with but modest computational burden (24, 6, 34, 32 and 25). The only shortcoming of the spatial approach is that its robustness decreases to zero as the quantile or outlyingness level is chosen farther out from the center (Dang and Serfling, 2010). This is especially detrimental to exploratory data analysis procedures such as detection of outliers and delineation of the “middle” 50%, 75%, or 90% of the data set, for example. Here we develop suitably robust versions using a trimming approach. The improvements in robustness are illustrated and characterized using simulated and actual data. Also, as a byproduct of the investigation, a new robust, affine equivariant, and computationally easy scatter estimator is introduced.     

Fluid flow pattern analysis in a trough region: a nonparametric approach

This paper aims at identifying statistically different circulation patterns characterising fluid flow in the trough region between two adjacent asymmetric waveforms, using the velocity data collected by 3D acoustic Doppler velocimeter. Statistical clustering has been performed using ideas originating from information theory and scale space theory in computer vision for splitting the trough region into different spatially connected segments (identifying the circulation bubble in the process) on the basis of circulation patterns. The paper attempts to visualise the fluid fluctuations in the trough region, with emphasis on the circulation region, by simulating the directional fluctuations of fluid particles from the kernel density estimates learned from the experimental data. The image representation of the estimate of the spatial turbulent kinetic energy (TKE) function reveals interesting features corresponding to the regions of high TKE, suggesting the possibilities for further research in this area along the lines of feature extraction and image analysis.     

Geriatric Care during Public Health Emergencies: Lessons Learned from Novel Corona Virus Disease (COVID-19) Pandemic

ABSTRACT

Geriatric care in public health emergencies is a serious concern, while, high case-fatalities among older adults across the globe in COVID-19 pandemic implies lack of preparedness. Most of the countries irrespective of developing and developed one enormously struggling because of an inchoate response system ignorant of geriatric health needs. Therefore, a robust approach is highly essential that requires an integrated emergency preparedness by addressing geriatric care.     

Single-step and multiple-step forecasting in one-dimensional single chirp signal using MCMC-based Bayesian analysis

Chirp signals are frequently used in different areas of science and engineering. MCMC-based Bayesian inference is done here for the purpose of one-step and multiple-step prediction in the case of the one-dimensional single chirp signal with iid error structure as well as dependent error structure with exponentially decaying covariances. We use Gibbs sampling technique and random walk MCMC to update the parameters. We perform total five simulation studies for the illustration purpose. We also do some real-data analysis to show how the method is working in practice.     

Matrix completion with nonconvex regularization: spectral operators and scalable algorithms

Statistics and Computing - In this paper, we study the popularly dubbed matrix completion problem, where the task is to “fill in” the unobserved entries of a matrix from a small subset...     

Sibling similarities and economic inequality in the US

I use a new methodological approach and larger US samples than previous studies and estimate that the sibling correlation across a range of economic outcomes is around 0.5. This suggests that half of economic inequality in the US can be attributed to family and community influences. A comparison with noneconomic outcomes suggests that individual choices rather than a simple mechanical relationship governs the intergenerational transmission of income. A decomposition of the sibling correlation suggests that the acquisition of human capital is an important channel through which family background affects future success but that noncognitive factors also play a role.