Contextual forces

A systemic view

In India many organisations are involved in tackling the wide range of interconnected problems related to poverty, human trafficking, sex work and HIV/AIDS. Five NGOs – one each located in Delhi and Kolkata (formerly Calcutta), and three in rural areas of northern India – have recently participated in a year-long action research study funded by the United Nations Development Programme (UNDP). The study aimed to identify the relevant agents and factors that contribute to these problems in each of the five research areas, and the relationships among them. With such knowledge, the NGOs hoped to be able to understand where they should target their campaigns, and thus design more effective interventions.

The study began with a national level workshop where the NGO staff explored the driving forces behind the increasing levels of poverty, migration and HIV/AIDS. They then created a preliminary version of a causal loop diagram to capture their understanding of the social context in which these processes take place.

After the workshop, fieldworkers from the NGOs visited the five action research areas, where they met with community representatives, sex workers, traffickers and pimps (middlemen) and the police to hear about the problem from their points of view. Based on this new information, they refined the original causal loop diagram, as explained in the following.

Creating a causal loop diagram

To create the preliminary causal loop diagram, the NGO workers and community representatives began by charting the incidence of poverty and the livelihood options available in each of the five research areas. It became clear that a lack of livelihood options results in poverty. Increasing poverty leads to a further loss of livelihood options, which in turn creates even more poverty. It is a vicious cycle – a causal loop – as shown in the diagram below. The plus sign in the centre indicates that the loop is self-reinforcing – a change in one of the variables produces a result that generates more of the same, either growth or decline.

In the diagram, the minus signs next to the two arrowheads indicate that the links between the variables – in this case poverty and livelihood options – are oppositional or balancing. In other words, increasing poverty will lead to fewer livelihood options, and fewer livelihood options will lead to more poverty. But as these links are oppositional, they can also mean that more livelihood options will lead to less poverty, and less poverty will lead to more livelihood options. The links reinforce each other, forming a feedback loop, which can be either positive or negative. Allow poverty to increase and livelihood options will decrease. But increase the livelihood options, and poverty will fall.

In India, many members of poor rural communities attempt to increase their livelihood options by migrating to the cities. This is a risky alternative, especially for women and girls (as well as boys) who are vulnerable to exploitation by traffickers who force them to work in the sex industry, where they are increasingly at risk of contracting HIV/AIDS.

 The growth of the sex industry means that increasing numbers of both sex workers and their clients are able to transmit the HIV virus, thus adding to the number of AIDS victims in this causal chain.

At the workshop, when this information was assembled, together with feedback links, the picture that emerged showed three reinforcing feedback loops: poverty–livelihoods, migration–sex work, and livelihoods–sex work–AIDS–poverty.

Just as in a machine where one set of gears drives another, which in turn drives another, these reinforcing loops will spin faster and faster until something is done to limit the factors that drive them. As long as there is migration and sex work is an option, these loops will continue to contribute to increasing levels of both poverty and HIV/AIDS.

The workshop participants continued their analysis and produced an even larger and more detailed causal loop diagram, focusing on the world of the sex workers, those who control the industry, and others (see below).

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Action Research Analysis Diagram

by TAHA Team & Sam Joseph

Causal loop diagram showing the context of poverty, migration and the sex industry in India. The women and children who migrate are particularly vulnerable to traffickers, and there are few incentives for rehabilitation. Note the large number of loops, the interconnections among them, and how some loops are driving others.

Breaking the link

Causal loop diagrams can be used to trace the causes and effects of a problem, or series of problems, and the feedback loops that perpetuate them. On the basis of this analysis, the Indian NGOs concluded that in order to reduce migration from rural areas, the only variable they would be able to change was the range of livelihood options. By promoting new economic activities in the rural areas (the top of the diagram), the NGOs hoped to help the farming communities by encouraging them to adopt new income-generating activities, thus reducing the high levels of poverty and eventually breaking the link between poverty and migration.

With a new range of targeted interventions, the NGOs achieved just that within one planting season. In two of the three rural areas, the new farming activities provided new opportunities for communities to improve their livelihoods so that fewer members of poor families needed to migrate to the cities. In the research areas in both Delhi and Kolkata, their interventions also resulted in higher incomes and improvements in the livelihoods of many poor families.

For the NGO workers, coming to understand the wide range of forces that serve to perpetuate a problem or situation, and realising that they could influence only a few of them, was a humbling experience. They also recognised that understanding the context at this broader level would contribute to much more meaningful project monitoring and evaluation (M&E). Usually M&E is inward-looking, focusing on individual projects without considering the broader picture.