Towards Bayesian Model-Based Demography Agency, Complexity and Uncertainty in Migration Studies
Material type:
ArticleSeries: Publication details: Bern Springer Nature Springer International Publishing [Imprint] 2021Description: 1 electronic resource (263 p.)Content type: - text
- computer
- online resource
- 9783030830397
- Interest qualifiers
- Relating to specific groups and cultures or social and cultural interests
- Relating to peoples: ethnic groups, indigenous peoples, cultures and other groupings of people
- Relating to migrant groups / diaspora communities or peoples
- Society and Social Sciences
- Society and culture: general
- Social and ethical issues
- Migration, immigration and emigration
- Sociology and anthropology
- Sociology
- Social research and statistics
- Population and demography
- 5 Interest qualifiers
- 5P Relating to specific groups and cultures or social and cultural interests
- 5PB Relating to peoples
- 5PBC Relating to migrant groups
- Agent-based modelling
- Bayesian demography
- Computational experiments
- Forced migration
- Free access
- J Society and Social Sciences
- JB Society and culture
- JBF Social and ethical issues
- JBFH Migration
- JH Sociology and anthropology
- JHB Sociology
- JHBC Social research and statistics
- JHBD Population and demography
- Migration modelling
- Model calibration and sensitivity
- Model-based approaches
- Open access
- Uncertainty quantification
- cultures and other groupings of people
- diaspora communities or peoples
- ethnic groups
- general
- immigration and emigration
- indigenous peoples
- thema EDItEUR
Open Access Unrestricted online access star
This 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.
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Creative Commons Licence cc by cc http://creativecommons.org/licenses/by/4.0/
eng
Freely available e-book