Suchergebnisse

[110] p. ; Imprint from STC. ; With an index. ; Cambridge University Library also has a fragment (Sayle 244) in the same types as and corresponding to leaves G2,3,6 and 7 in this edition but in a different setting with "villayne" while this edition has "vyllayne" on leaf G2r line 1--STC. ; Imperfect; lacks leaf D7. ; Signatures: A-G (-G8). ; Reproduction of the original in the Cambridge University Library.

Thomas d'Aquino* [OP] ; Volltext // Exemplar mit der Signatur: München, Bayerische Staatsbibliothek -- P.lat. 1925

Does the occurrence of flood disaster increase the risk of communal conflict and if so, does trust in state political institutions mitigate the adverse effect? This study addresses these questions by studying the intervening effect of trust in local governmental institutions at a sub-national level. The effect of flood disasters on the risk of communal violence is expected to be contingent on peoples' trust that local political structures are able to address potential disputes between groups. Violent conflicts, in that sense, are neither inevitable nor directly determined by the occurrence of disasters. They largely depend on the context of a given society and political response to these external shocks. To test this expectation, the study uses survey data on trust in local state institutions in Sub-Saharan Africa from the Afrobarometer (2005–2018), combined with geo-referenced communal conflict and flood data. In line with theoretical expectations, results suggest that flood disasters are associated with communal violence only for administrative districts that are governed by distrusted local state institutions. Conversely, flood disasters tend to be negatively associated with the risk of communal clashes in the presence of highly trusted local government councils and (especially) trusted judicial courts. Changing model specifications and estimation techniques produces similar results. An out-of-sample cross-validation also shows that accounting for political variables, in addition to flood disasters, improves the predictive performance of the model.