In 2018, Australia passed into the law the Modern Slavery Act, requiring companies to investigate and report on modern slavery in their supply chains. [1]
The OAASIS [2] project (the Open Analysis of Slavery in Supply Chains) aims to harness the power of input-output analysis to assist companies and governments to understand how slavery is embodied in the supply chains of goods and services that Australian's consume. OAASIS hopes also to build tools that help companies comply with the Act.
Part of this work is to assemble and compile a collection of tools that can be used to calculate modern slavery footprints. For example the make-labour-satellite python repo (https://github.com/modern-slavery-open-lib/make-labour-satellite) reads in several modern-slavery and 'problematic labour' datasets and casts them to the GLORIA MRIO [3] classification - enabling them to be used with GLORIA to calculate footprints [4]. The first datasets we have added is from Shilling (2021) [5] and also the ILO [6].
If you would like to be involved, or know of some good labour data, please reach out!
[1]: Modern Slavery Act: https://www.legislation.gov.au/Details/C2018A00153
[2]: The OAASIS project: https://www.sydney.edu.au/science/our-research/research-areas/physics/big-data-combatting-modern-slavery.html
[3]: GLORIA MRIO: https://ielab.info/analyse/gloria
[4]: The data is converted to the GLORIA classfication using the mapping operation: x'(1.p) = x(1.n) Msr(n.m) Msr(m.p)
[5]: Shilling et al., 2021, Modern slavery footprints in global supply chains, Journal of Industrial Ecology, https://doi.org/10.1111/jiec.13169
[6]: International Labour Organization: https://www.ilo.org/global/statistics-and-databases/lang--en/index.htm