Code 8.7: Finding Hidden Populations – Orphanage Trafficking

30 March 2019
Research Innovation

Paul Jones  | Visiting Researcher, The Alan Turing Institute
Chloe Setter  | Senior Advisor, Lumos

Code 8.7—an event designed by UN University Centre for Policy Research to bring together anti-slavery experts, computational science, AI and data specialists—presented an opportunity to explore new approaches to fighting modern slavery by hosting several “hothouses” in which experts were given a problem to brainstorm.

Our hothouse looked at on orphanage trafficking, a little-known form of child exploitation that involves children being recruited from families into residential institutions for the purpose of exploitation. Orphanages should be consigned to the history books. Yet in 2019, not only do they still exist, but they are actually on the rise in some parts of the world. This is despite more than 80 years of research proving the harm they cause to children and the increased cost compared with family-based care.

We began with presentations from the Lumos Foundation, describing what is currently known about orphanages globally. An estimated 8 million children are living in institutions around the world, but due to a lack of quality data, it’s suspected that the real number is far higher.

From left to right: Chloe Setter (Lumos), Kelly Gleason (UN University Centre for Policy Research), Chris Cuthbert (Lumos).

Many in the room were surprised to learn that around 80 per cent of children in institutions are not actually orphans, and that, in some instances, orphanage tourism—or voluntourism—seems to be a major driver of their recruitment. But how could we better understand this phenomenon that sees children being recruited from their families and placed into orphanages in order to drive donations, volunteers and visitors? How might we estimate the true scale of the orphanage business?

Through its work in Haiti, Lumos has been able to demonstrate huge quantities of funding going into orphanages in the country, where it is thought that 32,000 children reside in institutional care. Only 15 per cent of these orphanages are officially registered and evidence was uncovered of children being recruited from their families under the promise of a better life, while orphanage owners kept children in appalling conditions, profiting from their childcare “business”.  This is child trafficking, but it is not currently captured in any identification systems globally or prosecuted by law enforcement.

We enlisted the help of the tech and slavery experts at the hothouse to brainstorm in two groups. The first covered “defining, operationalizing and measuring orphanage trafficking” and the second looked at “technical solutions for finding hotspots, financial flows and data sources”.

In order to steer data collection, it is first necessary to define a clear set of indicators, or features, that are likely to be indicative of this type of trafficking. These could be manually validated with a variety of known cases, before attempting to construct any kind of data science model that may try to assign a level of “risk” to individual institutions or a risk model for vulnerable populations.

Such efforts must also be reconciled with the longer-term goal of working towards rehoming all institutionalized children in family-based care, rather than attempting to “rate” individual institutions, which can create an unhelpful perception of good versus bad orphanages.

A key theme that emerged from both groups was that of seeking new data collection opportunities to address the large knowledge gap that exists on this issue. Currently, data collection is spotty, relying heavily on small-scale interview and survey-based studies. New methods need to be considered, ideas included self-reporting (by staff, volunteers or even children in institutions), perhaps via secure websites or mobile applications, or amending existing surveys, such as the Global Slavery Index, to seek more evidence on this form of exploitation.

The use of satellite imagery—as was demonstrated in earlier sessions by the University of Nottingham’s Rights Lab in identifying brick kilns—was also discussed as a means of mapping unregistered institutions where trafficking may proliferate.

The participants also agreed that it would probably be most fruitful to focus on the data trail from orphanage tourists and voluntourists themselves, which is perhaps more easily obtainable, for instance through social media commentaries, online advertising and perhaps even through some kind of declaration of orphanage volunteering at immigration. Information could also be gleaned from the agencies and tour guides offering volunteering opportunities, perhaps summaries of where they are sending volunteers and also feedback from local guides working with the agencies.

Throughout the sessions, a variety of non-technical strategies to bring about change were also discussed. These included a focus on awareness campaigns for potential “voluntourists” (e.g. at schools, universities, travel companies) and attempting to change perceptions that persist implying children are better off in institutions or that there are no alternatives.

Participants left the session brimming with ideas and positive about how technology might help eradicate this outdated model of care and accompanying commodification of children. Many noted that this form of trafficking is unique in that it is largely enabled by well-intentioned funding and resources. This means that, as soon as people become aware of the issue, we are all a big step forward towards solving it.

Paul Jones is a visiting researcher at The Alan Turing Institute.

Chloe Setter is a senior advisor at Lumos.

This piece has been prepared as part of the Code 8.7 Conference Report. Read all the contributions here. Download the full PDF report here.

This article has been prepared by Paul Jones and Chloe Setter as contributors to Delta 8.7. As provided for in the Terms and Conditions of Use of Delta 8.7, the opinions expressed in this article are those of the authors and do not necessarily reflect those of UNU or its partners.

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