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001431233 001__ 1431233
001431233 003__ OCoLC
001431233 005__ 20230308003226.0
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001431233 020__ $$a9783030830397$$q(electronic bk.)
001431233 020__ $$a303083039X$$q(electronic bk.)
001431233 020__ $$z9783030830380
001431233 0247_ $$a10.1007/978-3-030-83039-7$$2doi
001431233 035__ $$aSP(OCoLC)1289494105
001431233 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dOCLCF$$dOCLCO$$dOCLCQ
001431233 049__ $$aISEA
001431233 050_4 $$aHB849.4$$b.B55 2022
001431233 08204 $$a304.6$$223
001431233 1001_ $$aBijak, Jakub,$$eauthor.
001431233 24510 $$aTowards Bayesian model-based demography :$$bagency, complexity and uncertainty in migration studies /$$cJakub Bijak ; with contributions by Philip A. Higham [and eight others].
001431233 264_1 $$aCham :$$bSpringer,$$c[2022]
001431233 264_4 $$c©2022
001431233 300__ $$a1 online resource (xxv, 263 pages) :$$bcolor illustrations
001431233 336__ $$atext$$btxt$$2rdacontent
001431233 337__ $$acomputer$$bc$$2rdamedia
001431233 338__ $$aonline resource$$bcr$$2rdacarrier
001431233 4901_ $$aMethodos series, methodological prospects in the social sciences ;$$vvolume 17
001431233 504__ $$aIncludes bibliographical references and index.
001431233 5050_ $$aPart I: Preliminaries: Chapter 1. Introduction -- Chapter 2. Uncertainty and complexity: towards model-based demography -- Part II: Elements of the modelling process -- Chapter 3. Principles and state of the art of agent-based migration modelling -- Chapter 4. Building a knowledge base for the model -- Chapter 5. Uncertainty quantification, model calibration and sensitivity -- Chapter 6. The boundaries of cognition and decision making -- Chapter 7. Agent-based modelling and simulation with domain-specific languages -- Part III: Model results, applications, and reflections -- Chapter 8. Towards more realistic models -- Chapter 9. Bayesian model-based approach: impact on science and policy -- Chapter 10. Open science, replicability, and transparency in modelling -- Chapter 11. Conclusions: towards a Bayesian modelling process.
001431233 5060_ $$aOpen access$$5GW5XE
001431233 520__ $$aThis open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration - one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.
001431233 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 20, 2021).
001431233 650_0 $$aDemography$$xMethodology.
001431233 650_0 $$aEmigration and immigration$$xSimulation methods.
001431233 650_6 $$aDémographie$$xMéthodologie.
001431233 650_6 $$aÉmigration et immigration$$xMéthodes de simulation.
001431233 655_0 $$aElectronic books.
001431233 830_0 $$aMethodos series ;$$vv. 17.
001431233 852__ $$bebk
001431233 85640 $$3Springer Nature$$uhttps://link.springer.com/10.1007/978-3-030-83039-7$$zOnline Access$$91397441.2
001431233 909CO $$ooai:library.usi.edu:1431233$$pGLOBAL_SET
001431233 980__ $$aBIB
001431233 980__ $$aEBOOK
001431233 982__ $$aEbook
001431233 983__ $$aOnline
001431233 994__ $$a92$$bISE