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The Governance Cycle in Parliamentary Democracies: A Computational Social Science Approach

Publication ,  Book
de Marchi, S; Laver, M
February 9, 2023

Parliamentary democracy involves a never-ending cycle of elections, government formations, and the need for governments to survive in potentially hostile environments. These conditions require members of any government to make decisions on a large number of issues, some of which sharply divide them. Officials resolve these divisions by 'logrolling'-conceding on issues they care less about, in exchange for reciprocal concessions on issues to which they attach more importance. Though realistically modeling this 'governance cycle' is beyond the scope of traditional formal analysis, this book attacks the problem computationally in two ways. Firstly, it models the behavior of "functionally rational" senior politicians who use informal decision heuristics to navigate their complex high stakes setting. Secondly, by applying computational methods to traditional game theory, it uses artificial intelligence to model how hyper-rational politicians might find strategies that are close to optimal. • Builds realistic but tractable computational models of government formation and survival • Shows how to build and test an agent-based model in a substantively important real-world setting • Represents the first application of computational social science to theoretical analysis in the social sciences.

Duke Scholars

DOI

Publication Date

February 9, 2023

Start / End Page

1 / 217
 

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de Marchi, S., & Laver, M. (2023). The Governance Cycle in Parliamentary Democracies: A Computational Social Science Approach (pp. 1–217). https://doi.org/10.1017/9781009315449
Marchi, S. de, and M. Laver. The Governance Cycle in Parliamentary Democracies: A Computational Social Science Approach, 2023. https://doi.org/10.1017/9781009315449.
de Marchi, S., and M. Laver. The Governance Cycle in Parliamentary Democracies: A Computational Social Science Approach. 2023, pp. 1–217. Scopus, doi:10.1017/9781009315449.

DOI

Publication Date

February 9, 2023

Start / End Page

1 / 217