Infrastructure Complexity welcomes submissions to the thematic series on Complexity in Migration.
Human migration has been empirically modeled across a number of domains such as geography, demography, economics and regional science. The primary purpose of migration models is to determine the behavior of migrants based on personal or household demographics and/or the characteristics of the migrant’s current location and those of potential destinations. These models attempt to find the determinants of a choice to migrate with an emphasis on job availability or wage maximization. Labor market imbalances are posited to induce migration flows, by attracting labor to cities with greater employment opportunities, and “repel” workers from places with fewer opportunities and lower wages.
More recently, given new possibilities from more detailed but also bigger data, the migrant has been modeled as an individual agent who chooses a city based on minimizing cost—often related to distance, or cost of living increases at the destination—and maximizing more general benefits—whether warmer weather for retirees, or a preponderance of single people, etc. Yet, these models still capture cities as an aggregation of census data that characterizes the city by numbers (e.g. average income), and sets of cities by the distance that lies between them.
With bigger data sets and more advanced computational methods, researchers can sidestep generalizing cities by parameters such as unemployment figures or average temperature, and instead, express cities as nominal, unique entities within a large spatial network of flows. This shift towards data-driven, systemic models of migration invites new ideas, new methods of analysis, and new research questions.
Although the methods may be innovative to the field of migration modeling, the objectives of their employment are the same: to show how people actually move and settle in certain places, and how the urban (county, neighborhood, country, etc.) network of migrants function and persist given variables of a city’s population size, distance, etc. Case studies may show how migration has changed over time, in correlation to external factors, such as the economic climate, political and regional fluxes, etc.
This thematic issue calls for contributions that uses systems and network science principles to model systems of migrants from place to place.
Potential topics include, but are not limited to:
- Network analysis
- Stochastic methods
- Bayesian statistics
- Transition probabilities
- Clustered hierarchies and community detection
- Temporal and spatial analysis
- Stationarity and resilience
- Probability distributions
Submission instructions
Before submitting your manuscript, please ensure you have carefully read the Instructions for Authors for Infrastructure Complexity. The complete manuscript should be submitted through the Infrastructure Complexity submission system. To ensure that you submit to the correct thematic series please select the appropriate section in the drop-down menu upon submission. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of the thematic series on Complexity in Migration. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.
Deadline for proposal
Please outline your research question, methods and goals (<300 words) and send to clio@psu.edu or bettencourt@santafe.edu.
Abstracts should be submitted by, 1 May 2016. Authors are encouraged to submit their abstracts before this date.
We look forward to issuing formal invitations to submit full papers upon receipt.
Deadline for submissions:
Completed manuscripts should be submitted in Editorial Manager by, 1 June 2016
Guest editors
Clio Andris, The Pennsylvania State University, USA
Luis Bettencourt, Santa Fe Institute, USA
Submissions will also benefit from the usual advantages of open access publication:
- Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient
- High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article
- No space constraints: Publishing online means unlimited space for figures, extensive data and video footage
- Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed
For editorial enquiries please contact editorial@infrastructure-complexity.com
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