Exploitation of vulnerableUndeclared employment groups such as refugees for cheap labour is a notorious phenomenon in Turkey. Up to 2017, only 1.3{%} of around 3 million Syrian refugees registered in Turkey have been granted a work permit, leaving the overwhelming majority dependent on undeclared employment with all its negative implications: high-risk jobs, pay below minimum wage and lack of access to social security. Mobile phone metadata allows for a detailed view on commuting routines and migration, possibly unearthing employment situations which are not captured otherwise. This study proposes a methodological framework for detecting fine-granular socio-economic occurrences in situations where little training data are available. As a proof of concept, the study applies the methodology to identify potentially undeclared employment among refugees in Turkey by analyzing seasonal migration and commuting patterns in two specific cases: during the late-summer hazelnut harvest in the province of Ordu and at the construction site of the Istanbul Airport. The study finds clear indication for work-related migration and commuting patterns among refugees hinting at undeclared employment. The proposed framework therefore provides an analytical instrument to make targeted interventions such as controls more effective by detecting small areas where undeclared work likely takes place
Refugees in Undeclared Employment—A Case Study in Turkey / Bruckschen, Fabian; Koebe, Till; Ludolph, Melina; Marino, Maria Francesca; Schmid, Timo. - ELETTRONICO. - (2019), pp. 329-346. [10.1007/978-3-030-12554-7_17]
Refugees in Undeclared Employment—A Case Study in Turkey
Marino, Maria Francesca;SCHMID, TIMO
2019
Abstract
Exploitation of vulnerableUndeclared employment groups such as refugees for cheap labour is a notorious phenomenon in Turkey. Up to 2017, only 1.3{%} of around 3 million Syrian refugees registered in Turkey have been granted a work permit, leaving the overwhelming majority dependent on undeclared employment with all its negative implications: high-risk jobs, pay below minimum wage and lack of access to social security. Mobile phone metadata allows for a detailed view on commuting routines and migration, possibly unearthing employment situations which are not captured otherwise. This study proposes a methodological framework for detecting fine-granular socio-economic occurrences in situations where little training data are available. As a proof of concept, the study applies the methodology to identify potentially undeclared employment among refugees in Turkey by analyzing seasonal migration and commuting patterns in two specific cases: during the late-summer hazelnut harvest in the province of Ordu and at the construction site of the Istanbul Airport. The study finds clear indication for work-related migration and commuting patterns among refugees hinting at undeclared employment. The proposed framework therefore provides an analytical instrument to make targeted interventions such as controls more effective by detecting small areas where undeclared work likely takes placeI documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.