Adultery, the Ground for Dissolution of Christian Marriage in Pakistan: Intersectional Constraint to Christian Women in Pakistan

Divorce from a distressful and unhappy marital alliance implies emancipation from perpetual pain, abuse, agony and violence but the social stigma attached to a divorced woman casts its shadow for life in the patriarchal and paternalistic socio-cultural settings in Pakistan. Seeking a judicial redress for dissolution of marriage is a legal right that needs to be available equally to both men and women. However, Christian married couples who apply for a divorce, are left with no options except to invoke the charge of adultery under Christian Divorce Act 1869. Proving adultery as a ground for dissolution of marriage stands as an impediment entailing character assassination of the accused and narrows the application of divorce on other grounds, such as domestic violence, abandonment by husbands and cruelty. The clergy representing Christian community fully supports the ground of adultery for dissolution of Christian marriage and vehemently opposes any position that calls for inclusion of nofault divorce. _________

A Methodology for Brand Name Hierarchical Clustering Based on Social Media Data

In the recent years, on the social media, the consumer perceptions are very necessary components of brand equity and marketing strategy. Normally, cluster analysis of different brand names is done in supermarkets and in huge- scale retail sector organizations. Clustering of brand names is a common technique for identification of different groups of brand names with maximum effectiveness and similarities. For example, items of different brand name regularly purchased together are located in one place on the shelf of a retail store. There are different techniques used for clustering. Among these techniques, the agglomerative hierarchical clustering technique builds a cluster hierarchy that is commonly displayed as a tree diagram called a dendrogram. In this study, I proposed a methodology for brand name clustering after collecting data from social media like Twitters. Data of garment products from Twitter is collected for experiments.In order to cluster the brand names, I calculated the distance of paired brand names based on the total number of occurrences of paired brands names mentioned together. Hierarchical clustering is used to find similarities among brand names. Finally, clusters of brand names are visualized through dendrogram. The dendrogram clearly shows the maximum similarities among brand names.