Policy and Complex Systems
more nuanced and more useful for policymakers , the parameters of the model could be expanded to account for more individual details among migrant populations and government policies . For example , more detail for describing migrant skill levels , more nuanced state policies ( e . g ., hybridization between economic and humanitarian policies ), and a better definition and representation for migrant “ vulnerability .” These expanded data elements could facilitate a more robust consideration of migrant motivations and enhance the model representation for government efforts and the resulting ability to detect potential trafficking victims . Greater fidelity in migrant attributes is necessary for a more realistic representation of the victim-centered approach .
Furthermore , several parameters in future iterations will be calibrated to existing data . For example , the current model imposes government immigration quotas . Implementing more precise representations and estimates of Germany ’ s migrant acceptance policies , rates , and limits may yield more representative insights . Similarly , the networks used to propagate perceptions across the agent population are highly stylized . These networks should be explored for a representation more realistic than assuming a preferential attachment network model .
Adding additional jurisdictions would also help us better understand the transnational elements of migration and human trafficking . Representing other governments would allow for a more complete exploration of the various factors that drive migrant perceptions ( e . g ., experiences in source and transit countries ) and recreate the more realistic complexities actual migrants face as they choose where to settle . Geopolitical dynamics could also be more fruitfully explored , such as the effects of closed-border policies in countries like
Hungary on more permissive policies , such as those in Germany .
Acknowledgments
The authors would like to express their appreciation for feedback on this research from Dr . Rob Axtell and Dr . Qing Tian from the Computational Social Science Program of the College of Science at George Mason University . We would also like to thank the anonymous reviewers for their constructive feedback .
References
Amin , S . ( 2010 ). A step towards modeling and destabilizing human trafficking networks using machine learning methods . Paper presentation , AAAI Spring Symposium Series , Palo Alto , CA , March 2010 . Retrieved from http :// www . aaai . org / ocs / index . php / SSS / SSS10 / paper / view / 1155 / 1341
Axtell , R . L ., & Epstein , J . M . ( 1994 ). Agent-based modeling : Understanding our creations . The Bulletin of the Santa Fe Institute , 28 – 32 .
Bagherpour , A ., Donaldson , S ., & Scharpnick , M . ( 2016 ). Europe at a crossroads : Pathways to mitigating the refugee crisis in 2016 . Washington , DC : Global Impact Strategies . Retrieved from https :// www . gistrat . com / wp-content / uploads / 2016 / 02 / giStrat _ EU _ Migration _ Feb _ 2016 . pdf
BBC News ( 2016 , March 4 ). Migrant crisis : Migration to Europe explained in seven charts . Retrieved from http :// www . bbc . com / news / world-europe-34131911
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