Suchergebnisse

Preface -- Contents -- Contributors -- Part I Perspectives on Agent-Based Modelling in Population Studies -- 1 Introduction: Agent-Based Modelling as a Tool to Advance Evolutionary Population Theory -- 1.1 Introduction -- 1.2 Two Concepts of Population -- 1.3 How Agent-Based Modelling May Bridge the Two Approaches to Population -- 1.3.1 The Macro-Micro-Macro Model and Agent-Based Modelling -- 1.3.2 Empirical Calibration -- 1.3.3 Avoiding Potential Pitfalls -- 1.3.4 Bridging the Gap -- 1.4 Contributions to Agent-Based Modelling in this Book

This book examines the use of agent-based modelling (ABM) in population studies, from concepts to applications, best practices to future developments. It features papers written by leading experts in the field that will help readers to better understand the usefulness of ABM for population projections, how ABM can be injected with empirical data to achieve a better match between model and reality, how geographic information can be fruitfully used in ABM, and how ABM results can be reported effectively and correctly. Coverage ranges from detailing the relation between ABM and existing paradigms in population studies to infusing agent-based models with empirical data. The papers show the benefits that ABM offers the field, including enhanced theory formation by better linking the micro level with the macro level, the ability to represent populations more adequately as complex systems, and the possibility to study rare events and the implications of alternative mechanisms in artificial laboratories. In addition, readers will discover guidelines and best practices with detailed examples of how to apply agent-based models in different areas of population research, including human mating behaviour, migration, and socio-structural determinants of health behaviours. Earlier versions of the papers in this book have been presented at the workshop "Recent Developments and Future Directions in Agent-Based Modelling in Population Studies," which took place at the University of Leuven (KU Leuven), Belgium, in September 2014. The book will contribute to the development of best practices in the field and will provide a solid point of reference for scholars who want to start using agent-based modelling in their own research

In Western countries, the distribution of relative incomes within marriages tends to be skewed in a remarkable way. Husbands usually do not only earn more than their female partners, but there is also a striking discontinuity in their relative contributions to the household income at the 50/50 point: many wives contribute just a bit less than or as much as their husbands, but few contribute more. This 'cliff' has been interpreted as evidence that men and women avoid situations where a wife would earn more than her husband, since this would go against traditional gender norms. In this paper, we use a simulation approach to model marriage markets and demonstrate that a cliff in the relative income distribution can also emerge without such avoidance. We feed our simulations with income data from 27 European countries. Results show that a cliff can emerge from inequalities in men's and women's average incomes, even if they do not attach special meaning to a situation in which a wife earns more than her husband.

AbstractIn response to the increasingly complex and heterogeneous immigrant communities settling in Europe, European countries have adopted various civic integration measures. Measures aiming to facilitate language acquisition are considered crucial for integration and cooperation between immigrants and natives. Simultaneously, the rapid expansion of social media usage is believed to change the factors affecting immigrants' language acquisition. However, only a few previous studies have analyzed whether this is the case. This article uses a novel longitudinal data source derived from Twitter to (1) analyze differences in the pace of immigrants' language acquisition depending on the migration policies of destination countries and (2) study how the relative sizes of the migrant groups in destination countries, and the linguistic and geographical distances between origin and destination countries, are associated with language acquisition. Results show that immigrants who live in countries with strict language acquisition requirements for immigrants and conservative citizenship policies have the highest median times until language acquisition. Based on Twitter data, we also find that language acquisition is associated with classic explanatory variables, such as the size of the immigrant group in the destination country and the linguistic and geographical distance between origin and destination country similar to the previous studies.

The emergence of disliking relations depends on how adolescents perceive the relative informal status of their peers. This phenomenon is examined on a longitudinal sample using dynamic network analysis (585 students across 16 classes in five schools). As hypothesized, individuals dislike those who they look down on (disdain), and conform to others by disliking those who they perceive as being looked down on by their peers (conformity). The inconsistency between status perceptions also leads to disliking, when individuals do not look up to those who they perceive to be admired by peers (frustration). Adolescents are not more likely to dislike those who they look up to (admiration). The results demonstrate the role of status perceptions on disliking tie formation.

Abstract
As online social activities have become increasingly important for people's lives, understanding how migrants integrate into online spaces is crucial for providing a more complete picture of integration processes. We curate a high-quality data set to quantify patterns of new online social connections among immigrants in the United States. Specifically, we focus on Twitter and leverage the unique features of these data, in combination with a propensity score matching technique, to isolate the effects of migration events on social network formation. The results indicate that migration events led to an expansion of migrants' networks of friends on Twitter in the destination country, relative to those of similar users who did not move. Male migrants between 19 and 29 years old who actively posted more tweets in English after migration also tended to have more local friends after migration compared to other demographic groups, indicating the impact of demographic characteristics and language skills on integration. The percentage of migrants' friends from their country of origin decreased in the first few years after migration and increased again in later years. Finally, unlike for migrants' friends' networks, which were under their control, we did not find any evidence that migration events expanded migrants' networks of followers in the destination country. While following users on Twitter in theory is not a geographically constrained process, our work shows that offline (re)location plays a significant role in the formation of online networks.