from Women Around the World , Women and Foreign Policy Program , and Human Trafficking

Modern Slavery Research Methods: Enabling Data-Driven Decisions

Child laborers eat their lunch after being rescued from squalid working conditions a sari embroidery factory, with the help of Nepalese police and child rights organizations, near Kathmandu, 2012. REUTERS/Navesh Chitrakar

This post is part of the Council on Foreign Relations’ blog series on human trafficking, in which CFR fellows and other leading experts assess new approaches to improve U.S. and global efforts to curb trafficking and modern slavery. This post was authored by Laura Gauer Bermudez, director of evidence and learning, April Stewart, senior evidence and learning associate, and Shannon Stewart, senior data scientist, and at the Global Fund to End Modern Slavery (GFEMS).

July 9, 2020

Child laborers eat their lunch after being rescued from squalid working conditions a sari embroidery factory, with the help of Nepalese police and child rights organizations, near Kathmandu, 2012. REUTERS/Navesh Chitrakar
Blog Post
Blog posts represent the views of CFR fellows and staff and not those of CFR, which takes no institutional positions.

This post is part of the Council on Foreign Relations’ blog series on human trafficking, in which CFR fellows and other leading experts assess new approaches to improve U.S. and global efforts to curb trafficking and modern slavery. This post was authored by Laura Gauer Bermudez, director of evidence and learning, April Stewart, senior evidence and learning associate, and Shannon Stewart, senior data scientist, and at the Global Fund to End Modern Slavery (GFEMS).

Modern slavery is a crime that is both hidden and embedded within the world around us. From the food we eat to the clothes we wear, our daily routines are likely only a few degrees of separation away from someone suffering under exploitative working conditions.

More on:

Human Trafficking

Labor and Employment

Child Marriage

Women and Women's Rights

Beyond labor exploitation in supply chains, modern slavery also exists through the commercial sexual exploitation of women and children and forced marriage. The International Labor Organization and Walk Free Foundation estimate forty million people are in modern slavery globally. Twenty-five million are in forced labor and fifteen million in forced marriage, with women and girls accounting for 71 percent of all cases of modern slavery. Due to the challenges in accessing and measuring these populations, experts consider such estimates to be conservative.  

Nevertheless, the breadth of exploitation indicated by that report has spurred governments and other key stakeholders to address the issue in more substantial ways. Foreign assistance agencies have begun to earmark funding to address modern slavery, new legislation on modern slavery has been enacted, and the private sector has begun to expand efforts to interrogate supply chains.

Yet, many stakeholders are taking actions while lacking the appropriate data to make targeted changes within their realm of influence. Though companies know that modern slavery is a problem globally, and have a sense that it could be hidden somewhere in their supply chains, the evidence needed to drive specific mitigation efforts often does not exist. To generate the evidence required to make data-driven decisions and to empower the private sector to make targeted changes, greater investments in modern slavery research need to be made.

Diversified research methods and partners are key to addressing a hidden phenomenon 

As a hidden phenomenon, many modern slavery experiences are difficult to measure in traditional ways. Victims are often isolated or too intimidated to come forward and may remain uncounted for months or years. Because modern slavery includes a spectrum of experiences, individuals can also pass in and out of the criteria required to be ‘counted’ as a victim, and, especially in cases of sexual exploitation, may reframe the experience several times. Such measurement challenges mean traditional research methods may not be capturing the full scope and scale of the problem, hindering informed policy or business decision-making. To better support evidenced-based decision-making, research efforts need to be diversified.

Prevalence estimation is one approach to modern slavery research. Scientifically sound prevalence estimation methods enable researchers to estimate the proportion of individuals within a given target population that are experiencing indicators of modern slavery. GFEMS works with researchers skilled in a number of prevalence estimation methods, including Respondent Driven Sampling (RDS), Network Scale-Up Method (NSUM), Time & Location Sampling (TLS), Probability Proportionate to Size (PPS) household sampling, and variations on and combinations of these methods, to achieve the most accurate estimate possible given the confines of measuring a hidden population.

More on:

Human Trafficking

Labor and Employment

Child Marriage

Women and Women's Rights

Despite its critical importance, modern slavery research efforts must go beyond prevalence estimation to capture the full picture of modern slavery globally. In the short term, quantitative insights from target populations using census or sample data can provide stakeholders with much needed point-in-time snapshots to make informed program, policy, or supply chain decisions. In the medium- and long-term, evaluative research designs can offer insights into the effectiveness of specific interventions designed to reduce or mitigate risks.

The way we capture such data is also evolving. As access to communications technology increases globally, GFEMS sees enhanced value in remote data collection using SMS, social media, and telephone surveys. Operating during the COVID-19 pandemic has reinforced the need to explore alternative channels for data collection, allowing GFEMS and its partners to remain engaged with workers and communities, identifying evolving needs and vulnerabilities.

Expanding beyond quantitative designs, qualitative information gathered from workers, survivors, community members, suppliers, law enforcement officials, and civil society organizations can provide critical background to support and provide context for quantitative data. Qualitative data helps build a narrative, bringing together the stories and first-person accounts of modern slavery, and aids the understanding of complex and interconnected systems perpetuating exploitation.

Research on modern slavery is not just the purview of academic institutions. Brands and suppliers in private sector supply chains can make data on modern slavery risk central to their decision-making. The deployment of worker voice mechanisms is an entry point to a comprehensive strategy of dialogue and engagement with workers. Data from these platforms can help businesses assess working conditions, flagging risk when indicated.

In addition, innovative techniques for analyzing large datasets are creating new opportunities and insights. Artificial intelligence is enabling data scientists to work with supply chain data and predict where forced labor may be more likely to occur, offering the private sector and regulatory bodies the opportunity to better target enhanced social audits, ramp up capacity building measures, and make better informed procurement decisions. Data analytics can also indicate when and where erratic purchasing or planning shortfalls may be putting undue pressure on suppliers, heightening the risk for slavery or slave-like conditions of workers to try and meet purchaser demand. Their ability to make tangible and significant impact in the way companies do business is a primary reason why GFEMS invests in risk detection techniques.

Whether it be via academic institutions, research firms, consultancy practices, communication companies, or in-house data science units within corporations, diversity and representation in research design, data collection, data analysis, and reporting of data on modern slavery makes for better research. For instance, putting female scientists front and center when examining modern slavery, particularly those issues disproportionately affecting women and girls, is one way to address this. Building research teams that better reflect the population under study— whether it be gender identity, ethnicity, minority status, religious affiliation, or sexual orientation—aids in a diversity of perspectives when framing research questions, survey items, design elements, and analytical frameworks, enabling teams to more comprehensively examine the social complexities and power imbalances underlying modern slavery.

Research findings should spur evidence-informed action

Evidence-informed decision-making to reduce modern slavery takes a variety of forms. Examples include corporate leadership supporting supply chain decisions based on data collected from worker voice platforms, government officials making data-driven budgeting decisions on modern slavery mitigations, financial institutions leveraging data analytics to efficiently flag potential illicit financial flows to traffickers, and civil society organizations designing community risk reduction messaging based on available evidence of what works.   

Though limited data have historically been a challenge for the anti-trafficking field, investment in diverse research methods can close the gap in actionable data. For there to be returns on investment in research, however, findings must be acted upon. As global stakeholders coalesce around evidence-informed action, coherent strategies can be forged and diverse efforts can be aligned with the goal of yielding substantial social change. Through consistent investment in action-oriented modern slavery research, GFEMS will continue to support evidence generation for maximum social impact.

Creative Commons
Creative Commons: Some rights reserved.
Close
This work is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License.
View License Detail
Close