What community dynamics encourage volunteering? Insights from Kenya

15/05/2014

Simon LewisSimon photo

Why is there a thriving culture of volunteering in one community while in another there’s hardly any voluntary action to be found? What are the community dynamics that encourage or discourage volunteering? These are some of the questions I have been trying to answer as part of the ‘Valuing Volunteering’ project. This is a global action research project, conducted by VSO in partnership with the Institute of Development Studiesto understand how, when and why volunteering affects poverty.

On a recent trip to Mombasa I was lucky enough to meet and work with members of the Volunteers In Action (VIA) Network – an umbrella group for volunteers on the Kenyan coast. The network looks to organise projects and events on issues of shared concern to volunteers and volunteer organisations; provides opportunities for volunteers to network and organically form their own groups and take forward their own projects; and puts on training directly in response to the needs identified by its members. It’s a passionate and enthusiastic group – something that cannot always be said for all similar groups in Kenya.

We looked to validate some of the findings that emerged from the participatory Systemic Action Research investigation conducted by the Valuing Volunteering Mombasa research group last year. During that exercise local researchers engaged people in three communities across Mombasa and found that the degree of volunteering taking place in each area varied greatly. Discussing this finding with members of the VIA Network, it came as no surprise.

Varying types of community produce different dynamics of volunteering
They see the varying dynamics of volunteering in different types of community across the city and appreciate that a community should not be viewed in isolation but also in terms of its interactions and relationships with other communities. For the purpose of this research project, we understand community to be very practically associated with a neighbourhood or an area that symbolically exists in the local consciousness (for example the local naming of neighbourhoods ).

The Valuing Volunteering research in 2013 found that, in Mombasa communities such as Shanzu and Kongowea, there was a limited amount of local volunteering taking place. Yes, there were some active local youth groups, but a resonating view amongst local community members was that development would not happen here. This collective sense of pessimism eroded social capital and discouraged volunteering. In contrast, research in Mombasa city centre revealed an active and vibrant volunteer environment with numerous volunteer involving organisations.

The discussion with VIA members supported these findings, but the interactions between communities in Mombasa (and the volunteers within them) exposed hidden layers of complexity. Deconstructing community dynamics in Mombasa, the group identified five broad categories of community and their relations to each other.

Five types of community diagram

 

1. Close knit-communities with high social capital– for example Frere Town in Mombasa, where residents feel a sense of personal investment in their community and often engage in volunteering within its boundaries (internal volunteering) for the good of the community.

2. Affluent urban centres– for example Mombasa city centre. Generally more affluent and home to higher numbers of volunteer involving organisations (particularly larger more formalised institutions) and businesses, the city exerts an influence on surrounding communities, pulling in migrants and commuters in search of work and volunteer opportunities.

3.Transitional communities–for example Mtwapa to the north of Mombasa where members are only temporary or semi-permanent residents. The high turnover of residents results in a lack of commitment to the long-term future of the community and acts to disincentivise volunteering.

4. Informal/less affluent urban and rural settlements– for example the two research locations of Shanzu and Kongowea. Critically, their existence is intertwined with that of the city centre, as residents are drawn to the perceived work and volunteer opportunities in central Mombasa. However, this adds depth to the initial finding that little volunteering takes place in such communities – it may be that there is little volunteering within the community but it is not the case that there are, by association, few volunteers. Instead, those volunteers are commuting to more affluent areas, such as Mombasa city centre, to take up more desirable and numerous volunteer opportunities. The effect is a drain on volunteers (particularly young volunteers) in the home community.

5. Rural/remote communities– cities such as Nairobi and Mombasa are the destination for many internal Kenyan migrants seeking employment, with many relocating from their rural homes. It is a common practice for Kenyans to support their families in the rural homestead through remittances, and some will return to the community to provide support, often in the form of volunteering, typically on a seasonal basis during holidays or later in life. Whilst some activities are successful and well-received, some returning volunteers have noted hostility to their acts of goodwill, particularly on cultural grounds as home communities perceive them as having changed or compromised their beliefs whilst away.

Analysing the dynamics of communities is useful in explaining why volunteering happens in some areas more than others. Crucially, it is not always the case that some communities have more volunteers than others but in some cases volunteers will commute or migrate to volunteer in areas where there are better opportunities or to avoid exploitation and being under-valued.

In the Kenyan context it is also critical to appreciate that the flows of volunteers are closely associated with the flows of people who move for employment opportunities – in fact volunteer and economic migrants/commuters are often the same people. When volunteers commute into the city centre from less affluent communities this is primarily because there is a greater pull factor emanating from the larger number and higher profile of volunteer organisations in the city centre that offer greater prospects for progression onto paid employment. The NGO sector is very desirable for paid employment in Kenya and, for many, volunteering represents a ‘stepping stone’ onto the employment ladder. As such volunteering in Kenya needs to be understood in relation to the factors that are driving the increasing urbanisation of its society and the complex relations and interconnections between its changing communities.

Simon Lewis is an international volunteer with VSO and the lead researcher for the IDS-VSO Partnership ‘Valuing Volunteering’ in Kenya. This is a slightly amended version of an article that previously appeared on the Valuing Volunteering Kenya blog.

Read more recent blogs from the Valuing Volunteering Project:


The Quiet Revolution of Participatory Numbers…

07/05/2014

Jane StevensJane_Stevens200

The very mention of statistics used to leave my mouth slightly dry and dredge up memories of unfathomable, confused hours in long-ago college lecture halls willing it all to be over. Mention participatory statistics however and the whole picture changes! Last week I heard more about this innovative approach to generating knowledge using numbers, at an IDS seminar given by Jeremy Holland, editor of the recently published book Who Counts: the power of participatory statistics.

It turns out that this quiet marriage of the qualitative and quantitative has been gently blossoming since the early 1990s, but is only now being considered by the mainstreams of research, monitoring and evaluation. Participatory research has long been established as a credible process that challenges ‘top-down’ approaches to knowledge generation.  By repositioning ownership and control it respects local knowledge and facilitates local ownership whilst also enabling collective reflection and action. The generation of participatory statistics has increasingly been woven into these processes to create what Jeremy describes as a win-win outcome for development. He emphasised how empowering it is for local people to engage in the generation of quantitative data which has traditionally been highly extractive and externally controlled. At the same time this way of working produces reliable, cost-effective statistics rooted in reality for aid and development agencies and donors.

In addition it underpins and validates qualitative insights. We heard an example whereby an over-enthusiastic researcher in a community, looking for an exaggerated outcome to reinforce their own preferences, was kept grounded by the accompanying participatory statistical data.  In this way participatory statistics can ‘rein us in’, and complement, qualify and add to the validity and credibility of qualitative research.

So, what participatory tools can we use to generate statistics?
Many existing methodologies lend themselves to this process: participatory mapping and modelling; proportional piling; card writing, marking, sorting, ordering and positioning; matrix ranking and scoring; pairwise ranking; linkage diagramming and pocket voting. All these, and more, can be combined to provide valuable ways of counting, calculating, measuring, estimating and comparing. Together they can provide rich sets of data, based on local knowledge, community-owned and accessible by all.

And unsurprisingly, where processes are genuine, there are other benefits. The actual process can be as important as the outcomes. In the seminar Jeremy told us how police and youth had come together in Kingston, Jamaica, to analyse the frequency and cyclical nature of violence in their ghetto communities. The process of working together on participatory statistics engendered a greater respect of each other and the shared understanding of positions and issues. Power issues are challenged too, as the question of who counts, who analyses, who interprets and whose narrative matters is addressed.

Work with and on participatory statistics certainly needs to be nuanced: methodologies need to be contextual, and adapt and evolve to suit circumstances. Importantly this way of working offers a world where those in power are more in touch with grass roots realities via locally generated statistics. And, from the context in which I work, one particular benefit stood out in the seminar discussions – participatory statistics can be used to measure qualitative change. This allows aid agencies and donors to embed reflective learning practice into accountability programmes whilst coming up with accurate and credible statistical data. Donor’s goalposts have shifted in recent years and they are increasingly demanding reporting against quantifiable achievements. Could participatory statistics provide a way to satisfy them, whilst not compromising on the complexity of processes and ideals that lead to the transformative social change we all wish to see?

Watch the video-recording of the seminar:

Jane Stevens works as communications officer in the Participation, Power and Social Chang Team at IDS. This blog draws on notes taken at the Seminar and the introduction of the book Who Counts.

Read a previous blog piece by Jane Stevens: