Abstract copyright UK Data Service and data collection copyright owner.

This study formed part of a time series in three countries (USA, Germany and UK) using a common core questionnaire.
Main Topics:

Variables
Measures of beliefs about a range of environmental issues; social and political values/paradigms; indices of behaviour on environmental issues, including political action; urgency of a range of problems; socio-demographic variables, including occupation and sector.

The data set includes the GIS coordination and population information of 18 potential service points (2 hospitals, 1 Red Crescent office, and 15 schools) together with 187 (109 villages and 78 neighbourhoods) main locations where Syrian refugees inhabit in the Kilis province in southern Turkey. Locations are classified as Villages (Köy) and Neighbourhoods (Mahalle) based on administrative divisions of Turkey. The population of each identified demand location, which is obtained from the local government in 2018, is provided as well.

The dataset has been used for a study on how to design a network of administrative facilities to support the roll-out of cash-based interventions, using refugee locations from the dataset to identify appropriate locations for these administrative facilities using the model presented in the paper. For decades the humanitarian sector has mainly relied on providing material assistance to beneficiaries during disaster relief. These days there is a growing importance in the provision of services, not only by means of replacing the distribution of relief items by cash & vouchers that can be exchanged for goods as needed but also in the provision of supporting services such as health or education. These services can help stimulate local market activity and restart livelihoods.

In this project we aim to design and implement the supply chain for two key services to beneficiaries: cash & voucher distribution (as a replacement for distributing core relief items).

The dataset has been used for a study on how to design a network of administrative facilities to support the roll-out of cash-based interventions, using refugee locations from the dataset to identify appropriate locations for these administrative facilities using the model presented in the paper.