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Drawing on a rich body of multimethod field research, this book examines the ways in which Indonesian and Philippine religious actors have fostered conflict resolution and under what conditions these efforts have been met with success or limited success.
The book addresses two central questions: In what ways, and to what extent, have post-conflict peacebuilding activities of Christian churches contributed to conflict transformation in Mindanao (Philippines) and Maluku (Indonesia)? And to what extent have these church-based efforts been affected by specific economic, political, or social contexts? Based on extensive fieldwork, the study operates with a nested, multi-dimensional, and multi-layered methodological concept which combines qualitative and quantitative methods. Major findings are that church-based peace activities do matter, that they have higher approval rates than state projects, and that they have fostered interreligious understanding.
Through innovative analysis, this book fills a lacuna in the study of ethno-religious conflicts. Informed by the novel Comparative Area Studies (CAS) approach, this book is strictly comparative, includes in-case and cross-case comparisons, and bridges disciplinary research with Area Studies. It will be of interest to academics in the fields of conflict and peacebuilding studies, interreligious dialogue, Southeast Asian Studies, and Asian Politics.
Zusammenfassende Darstellung der Ergebnisse einer empirischen Studie über Friedens- und Postkonfliktarbeit durch kirchliche Akteure in Indonesien ( Maluku) und auf den Philippinen (Mindanao). Auf Basis der Untersuchung ziehen die Autoren Schlussfolgerungen über die praktische Bedeutung kirchlicher Friedensprojekte nach Konflikten
Methodology
(2019)
Chapter three introduces the methodology of the study and the research design. Its nested, multi-layered methodological concept constitutes one of the major innovations of the book and enables us to map and measure peacebuilding activities of Christian church actors in the conflicts of Mindanao and Maluku (Ambon). The methodological concept draws from Katzenstein’s “analytic eclecticism,” which transcends the rigidity of existing research schools and seeks to fuse elements of several approaches into a new research agenda. The nested, multi-layered analysis of this book seamlessly combines process tracing, discourse analysis, statistical analysis of primary data generated in two field surveys, Qualitative Comparative Analysis (QCA), and statistical regression analysis.
Neural network representations of simple models, such as linear regression, are being studied increasingly to better understand the underlying principles of deep learning algorithms. However, neural representations of distributional regression models, such as the Cox model, have received little attention so far.We close this gap by proposing a framework for distributional regression using inverse flow transformations (DRIFT), which includes neural representations of the aforementioned models. We empirically demonstrate that the neural representations of models in DRIFT can serve as a substitute for their classical statistical counterparts in several applications involving continuous, ordered, timeseries, and survival outcomes. We confirm that models in DRIFT empirically match the performance of several statistical methods in terms of estimation of partial effects, prediction, and aleatoric uncertainty quantification. DRIFT covers both interpretable statistical models and flexible neural networks opening up new avenues in both statistical modeling and deep learning.
