The new Domestic Workers Dataset is the largest single set of surveys (n = 11,759) of domestic workers to date. Our analysis of this dataset reveals features about the lives and work of this "hard-to-find" population in India—a country estimated to have the largest number of people living in forms of contemporary slavery (11 million). The data allow us to identify child labour, indicators of forced labour, and patterns of exploitation—including labour paid below the minimum wage—using bivariate analysis, factor analysis, and spatial analysis. The dataset also helps to advance our understanding of how to measure labour exploitation and modern slavery by showing the value of "found data" and participatory and citizen science approaches.
Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no 689812.
The most recent Global Slavery Index estimates that there are 40.3 million people enslaved globally. The UN's Agenda 2030 for Sustainable Development Goal number 8, section 8.7 specifically refers to the issue of forced labour: ending modern slavery and human trafficking, including child labour, in all forms by 2025. Although there is a global political commitment to ending slavery, one of the biggest barriers to doing so is having reliable and timely, spatially explicit and scalable data on slavery activity. The lack of these data compromises evidence-based action and policy formulation. Thus, to meet the challenge of ending modern slavery new and innovative approaches, with an emphasis on efficient use of resources (including financial) are needed. This paper demonstrates the fundamental role of remote sensing as a source of evidence. We provide an estimate of the number of brick kilns across the 'Brick Belt' that runs across south Asia. This is important because these brick kilns are known sites of modern-day slavery. This paper reports the first rigorous estimate of the number of brick kilns present and does so using a robust method that can be easily adopted by key agencies for evidence-based action (i.e. NGOs etc) and is based on freely available and accessible remotely sensed data. From this estimate we can not only calculate the scale of the slavery problem in the Brick Belt, but also calculate the impact of slavery beyond that of the enslaved people themselves, on, for example, environmental change and impacts on ecosystem services – this links to other Sustainable Development Goals. As the process of achieving key Sustainable Development Goal targets will show, there are global benefits to ending slavery - this will mean a better world for everyone: safer, greener, more prosperous, and more equal. This is termed here a Freedom Dividend.
Recent estimates suggest that more than 40 million people worldwide are in situations of modern slavery and other forms of labor exploitation. UN Sustainable Development Goal 8.7 addresses this problem and urges stakeholders to take effective measures to end all forms of labor exploitation by 2030. Labor exploitation is often a direct consequence of forced migration, and humanitarian operations have a key role to play in tackling this issue worldwide. Academic research can facilitate this by providing the necessary decision-making tools to support antislavery practitioners in humanitarian organizations and governments. For effective resource allocation, these practitioners need tools to help them systematically identify and assess the risks of labor exploitation in an area. In this paper, we develop a multi-method approach that combines various data sources to capture the issue's complex and multidimensional nature. Through satellite remote sensing, we first identify 50 informal settlements hosting migrant workers in the strawberry production area of Southern Greece. We then apply a multi-criteria decision analysis (MCDA) method to a subset of six informal settlements in order to evaluate their labor exploitation risks based on eight criteria. In addition to being practically implemented by a humanitarian organization and a government agency in Greece, our paper advances research on humanitarian operations and labor exploitation by elucidating how a multi-method approach can be used for data-driven prioritization of interventions against labor exploitation. Our approach offers opportunities for other applications in the field of humanitarian operations.
A strong relationship between night-time light (NTL) data and the areal extent of urbanized regions has been observed frequently. As urban regions have an important vertical dimension, it is hypothesized that the strength of the relationship with NTL can be increased by consideration of the volume rather than simply the area of urbanized land. Relationships between NTL and the area and volume of urbanized land were determined for a set of towns and cities in the UK, the conterminous states of the USA and countries of the European Union. Strong relationships between NTL and the area urbanized were observed, with correlation coefficients ranging from 0.9282 to 0.9446. Higher correlation coefficients were observed for the relationship between NTL and urban building volume, ranging from 0.9548 to 0.9604; The difference in the correlations obtained with volume and with area was statistically significant at the 95% level of confidence. Studies using NTL data may be strengthened by consideration of the volume rather than just area of urbanized land.
In: Whitfield , S , Beauchamp , E , Boyd , D , Burslem , D , Byg , A , Colledge , F , Cutler , M , Didena , M , Dougill , A , Foody , G , Godbold , J , Hazenbosch , M , Hirons , M , Speranza , C , Jew , E , Lacambra , C , Mkwambisi , D , Moges , A , Morel , A , Morris , R , Novo , P , Rueda , M , Smith , H , Solan , M , Spencer , T , Thornton , A , Touza , J & White , P 2019 , ' Exploring temporality in socio-ecological resilience through experiences of the 2015-16 El Niño across the Tropics ' , Global Environmental Change , vol. 55 , pp. 1-14 . https://doi.org/10.1016/j.gloenvcha.2019.01.004
In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is high, the frequency, duration, and trends in these fluctuations are important determinants of socio-ecological resilience. In this paper, the dynamics of six diverse socio-ecological systems (SES) across the Tropics – ranging from agricultural and horticultural systems in Africa and Oceania to managed forests in South East Asia and coastal systems in South America – are examined in relation to the 2015–16 El Niño, and the longer context of climatic variability in which this short-term 'event' occurred. In each case, details of the socio-ecological characteristics of the systems and the climate phenomena experienced during the El Niño event are described and reflections on the observed impacts of, and responses to it are presented. Drawing on these cases, we argue that SES resilience (or lack of) is, in part, a product of both long-term historical trends, as well as short-term shocks within this history. Political and economic lock-ins and dependencies, and the memory and social learning that originates from past experience, all contribute to contemporary system resilience. We propose that the experiences of climate shocks can provide a window of insight into future ecosystem responses and, when combined with historical perspectives and learning from multiple contexts and cases, can be an important foundation for efforts to build appropriate long-term resilience strategies to mediate impacts of changing and uncertain climates.
Funding: This work was supported by the UK Natural Environment Research Council and the UK Government Department for International Development [grant numbers NE/P004806/1; NE/P004091/1; NE/P00394X/1; NE/P004210/1; NE/P004830/1; NE/P003974/1]. Acknowledgment We are grateful to Annalyse Moskeland for her valuable support in the organisation and running of the workshop. ; Peer reviewed ; Publisher PDF
In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is high, the frequency, duration, and trends in these fluctuations are important determinants of socio-ecological resilience. In this paper, the dynamics of six diverse socio-ecological systems (SES) across the Tropics – ranging from agricultural and horticultural systems in Africa and Oceania to managed forests in South East Asia and coastal systems in South America – are examined in relation to the 2015–16 El Niño, and the longer context of climatic variability in which this short-term 'event' occurred. In each case, details of the socio-ecological characteristics of the systems and the climate phenomena experienced during the El Niño event are described and reflections on the observed impacts of, and responses to it are presented. Drawing on these cases, we argue that SES resilience (or lack of) is, in part, a product of both long-term historical trends, as well as short-term shocks within this history. Political and economic lock-ins and dependencies, and the memory and social learning that originates from past experience, all contribute to contemporary system resilience. We propose that the experiences of climate shocks can provide a window of insight into future ecosystem responses and, when combined with historical perspectives and learning from multiple contexts and cases, can be an important foundation for efforts to build appropriate long-term resilience strategies to mediate impacts of changing and uncertain climates.
In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is high, the frequency, duration, and trends in these fluctuations are important determinants of socio-ecological resilience. In this paper, the dynamics of six diverse socio-ecological systems (SES) across the Tropics – ranging from agricultural and horticultural systems in Africa and Oceania to managed forests in South East Asia and coastal systems in South America – are examined in relation to the 2015-16 El Niño, and the longer context of climatic variability in which this short-term 'event' occurred. In each case, details of the socio-ecological characteristics of the systems and the climate phenomena experienced during the El Niño 48 event are described and reflections on the observed impacts of, and responses to it are presented. Drawing on these cases, we argue that SES resilience (or lack of) is, in part, a product of both long-term historical trends, as well as short terms shocks within this history. Political and economic lock-ins and dependencies, and the memory and social learning that originates from past experience, all contribute to contemporary system resilience. We propose that the experiences of climate shocks can provide a window of insight into future ecosystem responses and, when combined with historical perspectives and learning from multiple contexts and cases, can be an important foundation for efforts to build appropriate long-term resilience strategies to mediate changing and uncertain climates.
In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is high, the frequency, duration, and trends in these fluctuations are important determinants of socio-ecological resilience. In this paper, the dynamics of six diverse socio-ecological systems (SES) across the Tropics – ranging from agricultural and horticultural systems in Africa and Oceania to managed forests in South East Asia and coastal systems in South America – are examined in relation to the 2015–16 El Niño, and the longer context of climatic variability in which this short-term 'event' occurred. In each case, details of the socio-ecological characteristics of the systems and the climate phenomena experienced during the El Niño event are described and reflections on the observed impacts of, and responses to it are presented. Drawing on these cases, we argue that SES resilience (or lack of) is, in part, a product of both long-term historical trends, as well as short-term shocks within this history. Political and economic lock-ins and dependencies, and the memory and social learning that originates from past experience, all contribute to contemporary system resilience. We propose that the experiences of climate shocks can provide a window of insight into future ecosystem responses and, when combined with historical perspectives and learning from multiple contexts and cases, can be an important foundation for efforts to build appropriate long-term resilience strategies to mediate impacts of changing and uncertain climates.
In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is high, the frequency, duration, and trends in these fluctuations are important determinants of socio-ecological resilience. In this paper, the dynamics of six diverse socio-ecological systems (SES) across the Tropics – ranging from agricultural and horticultural systems in Africa and Oceania to managed forests in South East Asia and coastal systems in South America – are examined in relation to the 2015–16 El Niño, and the longer context of climatic variability in which this short-term 'event' occurred. In each case, details of the socio-ecological characteristics of the systems and the climate phenomena experienced during the El Niño event are described and reflections on the observed impacts of, and responses to it are presented. Drawing on these cases, we argue that SES resilience (or lack of) is, in part, a product of both long-term historical trends, as well as short-term shocks within this history. Political and economic lock-ins and dependencies, and the memory and social learning that originates from past experience, all contribute to contemporary system resilience. We propose that the experiences of climate shocks can provide a window of insight into future ecosystem responses and, when combined with historical perspectives and learning from multiple contexts and cases, can be an important foundation for efforts to build appropriate long-term resilience strategies to mediate impacts of changing and uncertain climates.
