Assessing modern slavery in global supply chains

Summary

This project will employ multi-region input-output analysis and a comprehensive global database (Lenzen et al. 2012a; Lenzen et al. 2013; Lenzen et al. 2017) to trace modern slavery in global supply chains. NOTE THAT this project is part of the larger research project: Enlisting the power of big data visualisation to help stamp out slavery in the supply chain. You will work in a team of interdisciplinary experts in data visualisation to construct a virtual reality environment driven by global data on modern slavery. In particular your research project will focus on undertaking a supply chain assessment using an input-output matrix of the global economy to identify modern slavery hotspots. 

The PhD candidate will be supervised by Dr Arunima Malik (Integrated Sustainability Analysis (ISA), School of Physics) and Dr Joy Murray (Integrated Sustainability Analysis). The applicant will join a multidisciplinary team based with the ISA Research Group at the School of Physics . 

ISA develops leading-edge research and applications for environmental, social and economic sustainability issues, bringing together expertise in environmental science, economics, technology, and social science.

Supervisor(s)

Dr Joy Murray, Dr Arunima Malik

Research Location

School of Physics

Program Type

PHD

Synopsis

Modern Slavery affects around 43 million people, more than at any time in recorded history (Global Slavery Index, 2018) and while jurisdictions worldwide are realising the need to take action there is mixed response from producers and consumers. The plight of workers in many supply chains is dire, particularly in textiles, seafood, agriculture, construction, manufacturing and mining. Inequities cover environmental as well as social issues and include biodiversity loss, carbon emissions, particulate matter, water use, waste, inequality, poverty, occupational safety and health; and child labour and slavery. The focus of this study is on modern slavery however the virtual reality architecture will be built so that other social and environmental supply chain issues can be addressed in future.  

The project will use multi-region input-output (MRIO) analysis and one of the world’s most powerful databases of the global economy – the global IELab (Lenzen et al. 2012a; Lenzen et al. 2013; Lenzen et al. 2017). 

The IELab provides a platform for combining detailed bottom-up process information about the system under study (i.e. in this case modern slavery) with comprehensive top-down input-output data on the background economy (Minx et al. 2009; Wiedmann 2009). The project requires collection of data on slavery from a wide range of sources (e.g. ILO; Global Slavery Index; Global Estimates of Modern Slavery; US funded International Organization for Migration’s Counter-Trafficking Module Database; annual EU list of geographical and sector hotspots of slavery). Inserted into the IELab these data will provide the data feeds for creating graphical representation of supply chains and illuminating where slavery exists. The resulting input-output-assisted ‘slavery footprint’ will become part of an existing suite of social IO applications (see for example Malik et al., 2018; Murray et al., 2018; Alsamawi et al. 2017; Alsamawi et al. 2017a; Alsamawi et al. 2017b; Alsamawi et al., 2014; Alsamawi et al. 2017; Hui et al. 2017; Xiao et al. 2016; Xiao et al. 2016a; Hoekstra 2010). However, VR visualisation of the slavery footprint will break completely new ground. 

This project has the power to transform lives.

Additional Information

This is not a funded position.  Applicant is responsible for obtaining a stipend if needed.

Interest and prior engagement in broader sustainability will be beneficial.

HDR Inherent Requirements

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:

- Confidential disclosure and registration of a disability that may hinder your performance in your degree;
- Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
- Ability to perform independently and/or with minimal supervision;
- Ability to undertake certain physical tasks (e.g. heavy lifting);
- Ability to undertake observatory, sensory and communication tasks;
- Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
- Ability to work in confined spaces or at heights;
- Ability to operate heavy machinery (e.g. farming equipment);
- Hold or acquire an Australian driver’s licence;
- Hold a current scuba diving license;
- Hold a current Working with Children Check;
- Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Keywords

input-output analysis, Virtual Reality, data visualisation, social effects of trade, supply chain analysis, MRIO

Opportunity ID

The opportunity ID for this research opportunity is: 2483

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