Discuss how qualitative methods can be used together with


- use your understanding of internal validity to critique the causal conclusions in the Lyons & Lowery article (that "government consolidation/fragmentation" CAUSED residents to be "more informed," "more satisfied,") in terms of specific "plausible alternative explanations" (this is what all "threats to internal validity are). To be clear, don't just say that history or selection threats could explain the observed findings-for each relevant threat provide a story of how that threat could lead to misleading conclusions about the impact of government consolidation or fragmentation.

- Then discuss how qualitative methods can be used together with quantitative methods by discussing the logic of mixed methods (in Caracelli& Greene), addressing issues such as ontology, epistemology, & ideology, induction & deduction, and (if you can) molar & molecular notions of causality.

- present the Caracelli& Greene approach, with examples of each of their Component approaches (triangulation, complementary, & expansion) and ONE of their Integrated (iterative, embedded or nested, holistic, & transformative) types.

- discuss how you would use mixed methods (being careful to use one type of Qualitative Field Research and one of the Caracelli& Greene types of mixed methods) in redesigning the Lyons & Lowery study; what would be its strengths and limits?

- use your understanding of designs and internal validity to explain how you would have designed a multiple times series study of the impact of governance structure (this would require that you started collecting data your outcomes measures a couple of years before a city changed from consolidated to fragmented, or vice versa) on residents being "informed" and "satisfied with local government." Be sure to note which threats to internal validity ARE and ARE NOT problematic when using a multiple time series design and, specifically, which threats that are concerning for the original Lyons & Lowery study that would not be a concern with the multiple time series design
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