A Catechumenate for the Korean Methodist Church: Ressourcement, Formation and a Response to Secularism and Korean Traditional Religions

Research by Korean sociologists of religion indicates that Korean Protestantism has lost much of the spiritual vitality of preceding generations and that it increasingly shows the influences of Korean shamanism, Neo-Confucianism, and Western secularism and consumerism. Suggestions in the areas of homiletics and Christian social ethics have been offered to help steer the Korean Protestant churches away from these worldviews toward a more biblically-based course. Drawing upon and expanding these earlier studies and proposals, the current work recommends another method for developing a biblically-based, spiritually-revitalized, baptismally-shaped and ministry-committed Protestantism in Korea: a pre-baptismal adult catechumenate, in this case one designed for the context of the Korean Methodist Church. In order to produce a renewed catechumenal structure for Korean Methodism, adult catechumenal processes as well as baptismal theologies and rites are examined and analyzed from three principal sources: the first five centuries of the Christian church, and especially the mystagogical literature of the fourth century; the Roman Catholic Rite of Christian Initiation of Adults developed after the Second Vatican Council; and the United Methodist Church in the United States, both texts officially authorized by the denomination's General Conference and unofficial materials, among them resources for an adult catechumenate in the Come to the Waters series. In addition, previous and current practices of preparation for baptism in the Korean Methodist Church are identified and critiqued. From these findings a set of principles is put forward that guide the proposed catechumenal structure.

Self-Organizing Grammar Induction Using a Neural Network Model

This paper presents a self-organizing, real-time, hierarchical neural network model of sequential processing, and shows how it can be used to induce recognition codes corresponding to word categories and elementary grammatical structures. The model, first introduced in Mannes (1992), learns to recognize, store, and recall sequences of unitized patterns in a stable manner, either using short-term memory alone, or using long-term memory weights. Memory capacity is only limited by the number of nodes provided. Sequences are mapped to unitized patterns, making the model suitable for hierarchical operation. By using multiple modules arranged in a hierarchy and a simple mapping between output of lower levels and the input of higher levels, the induction of codes representing word category and simple phrase structures is an emergent property of the model. Simulation results are reported to illustrate this behavior.