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Community Survey Final Report

Banan Project - Cycle One

February – May 2016

Cambodia

Research conducted by: Charlie Hinton, Thol Heng, Sum Sichoeurn, Julia Herritty, Polin Dy, Bex Idriss, Kate Goodrum, Soramony Soung, Chantel Davies, Karis Lambert, Khaem Peak,

Franzi Koefer, Keavon Meas, Lwiza Mulenga, Veasna Veurn, Joshua Shelley, Bunthorn Chhorn and Dani Waddell

Written by Franzi Koefer and Joshua Shelley

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Contents Page:

Introduction 3Limitations of the Methodology 4Community Survey Demographic Breakdown 5Data Collection Method and Survey Breakdown 6By Village – Findings Overview – Figure 1 8By Village – Findings Breakdown 9The Issue of Migrating Adults – Findings Overview – Figure 2 11The Issue of Migrating Adults – Findings Breakdown 12Local Economic Environment - Overview 15Debt and Borrowing – Findings Breakdown – Figures 3, 4, 5, 6, 7 15Migration and Employment Skills – Findings Breakdown – Figures 8, 9, 10 19Potential Avenues for Future Research 20Criticisms of the Process and Points for Improvement 21Conclusion 22

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Introduction:

Our primary aim when conducting our community surveying exercise was to gain a better understanding of the problems and specific day-to-day living context of the residents of Phnom Sompov, focusing on three villages; Sompov Kert, Sam Nanh and K’Downg. Using the questionnaire provided we collected both qualitative and quantitative data by interviewing the heads of households we selected randomly, and have subsequently analysed the data to attempt to establish correlations and suggest potential causality for these correlations. The first perspective we adopted was analyzing the data by village, and the second perspective by families who had adults working away from the community for more than 9 months per year; this will be expanded upon subsequently. Ultimately, we hope that this report will contribute to informing the future of the project when deciding the direction in which VSO ICS volunteers can work with the community to improve their day-to-day lives.

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Limitations of the Methodology:

During the collection and analysis of the data collected we met with several difficulties that should be kept in mind when interpreting our data and drawing conclusions from the report. Where possible however, these are taken into account when identifying correlations and making assumptions.

Questions may have been misunderstood by the participants, therefore skewing their answers and meaning the data collected did not represent their true opinion. This may have been down to confusion either on the part of the participant or a lack of capacity for clear explanation on the part of those conducting the surveys. For example, the volume of data collected in the ‘Resilience and Exposure to Shocks’ is significantly lower than in the other sections. This is because of the complicated nature of the question, involving perceived frequency of events and many different options to choose from. Therefore, conclusions drawn from this section are not as representative or therefore valuable, however we feel that the data we did have was as a result of clear understanding.

Although difficult to assess, there is the possibility that households may have not answered some of the more sensitive questions truthfully. This could be for a variety of reasons, such as embarrassment or in an attempt to draw particular focus from the project to their household, among others.

Although a relatively minor disparity, different numbers of households were interviewed in each village (Sompov Kert – 50 households, Sam Nanh – 45 households, K’Downg – 41 Households). Again, this should be taken into consideration when assessing the representativeness of the data from each village.

The structuring of the data grouping is also potentially flawed. For example, some of the houses in Sompov Kert are closer to some houses in K’Downg than they are to houses at the other side of Sompov Kert. This is important because when considering a category such as water availability, households may have more in common with houses in villages other than their own in terms of the issues they face, but this is missed by the village boundaries put in place, potentially devaluing the separation of the data by village.

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Community Survey Demographic Breakdown:

Villages surveyed: Sompov Kert, Sam Nanh and K’Downg

Number of Households surveyed: 136

Average respondent's age (years): 53

Average head of Households age (years): 55

Gender statistics

Total: 134

Male respondents: 38

Female respondents: 96

Total: 130

Male headed Household: 99

Female headed Household: 31

Female & Male joint headed Household: 0

Head of household's marital status

Total: 120

Married: 92 (83 males, 7 females)

Single: 4 (3 males, 1 female)

Divorced: 13 (3 males, 10 females)

Widowed: 12 (1 male, 11 females)

Comments:

The prevalence of female heads of households who identified as either single, divorced or widowed suggests two things; firstly, that females are unlikely to be the head of their household if they are married, and secondly that males are possibly more likely to remarry than females if they become divorced or widowed, explaining the disproportionate male/female split in these two categories. Anecdotal evidence suggests that while newly single men may occasionally remarry much younger women, it is extremely rare to remarry with someone who already has children from a previous relationship. Therefore, it is reasonable to suggest that a strongly patriarchal culture seems to exist within the community.

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Data Collection Method and Survey Breakdown:

Each poverty component category was broken down into multiple subsections, with the calculations that produced scores between 0-100 (0 reflecting a poor quality of life in the category and 100 reflecting a healthy quality of life) informed by specific parts of the questionnaire:

Food & Nutrition Security

Consumption Q33.1Q33.2

Access Stability Q33.3Q33.4

Nutrition Quality Q34.1Q34.2Q34.3Q34.4Q34.5Q34.6Q34.7

Domestic Water Supply

Quality Q14.3Q19Q16

Availability Q17.1Q17.2

Access Q15Q18

Sanitation & Hygiene Toilet Facility Q11.1Q11.2

Household waste management

Q12.1Q12.2Q12.3

Hygiene Practices Q13.1Q13.2Q13.3

Farm Assets Land Tenure Q20Q21Q27

Land Quality Q22.1Q22.2

Crop Inputs Q23.1Q23.2Q23.3aQ23.3bQ26

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Livestock/Aquaculture Inputs

Q24.1aQ24.1bQ24.2Q25.1aQ25.1bQ25.2

Non-Farm Assets Employment & Skills Q35.1

Q35.2

Financial Services Q36

Q37.1

Q37.2

Fixed Assets & Remittances

Q2/(Q1.1+Q1.2)

Q9.2

Q39

Exposure & Resilience to Shocks

Degree of Exposure Q28.1Q29.1Q30.1Q28.2Q29.2Q30.2

Coping Ability Q31.1Q31.2Q31.3

Recovery Ability Q32.1Q32.2Q32.3

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By Village - Findings Overview:

The first perspective that we adopted to analyse the data was by village, in order to try to get a better idea of the different demographics and issues faced in Sompov Kert, Sam Nanh and K’Downg. Following the presentation of our findings when using the separate villages as our variable, we hope that a deeper understanding of the geographical context of the region can be developed, meaning that future community initiatives can be more specifically targeted.

Figure 1 Radar Graph showing score /100 by village and poverty component

Comments:

There is a need to not only take into account the differentiation of scores between villages, but to view the scores from a broader perspective in relation to other poverty components. For example, when viewing the scores by village in regards to the Food and Nutrition Security component, the disparity of score is one of the highest of all the components. However, the category as a whole has a high score relative to other poverty components such as Non-Farm Assets, and this should be kept in mind when targeting which area to focus on.

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By Village – Findings Breakdown:

We will now provide a detailed breakdown of each poverty component by village with notable differences in score, including the score by subsection. We adopted a colour coding scheme as follows:

Blue – The village with the highest score Green – The village with the middling score Red – The village with the lowest score

Food and Nutrition Security Component:

- The pattern in the Food and Nutrition Security component is clear. Sompov Kert scores highest in each of the three categories, and scores at least 11.5 or higher than K’Downg in each Category. Sam Nanh scores generally fall half way between the scores of the two villages.

- In comparison to the other categories nutrition quality is fairly poor, especially in Sam Nanh and K’Downg.

Domestic Water Supply Component:

- Water quality and availability is worse in Sompov Kert than in K’Downg and Sam Nanh. Water access, however, is better in Sompov Kert than in other villages.

- Relatively, scores for domestic water supply are very low.

Sub-Section Sompov Kert Sam Nanh K’DowngConsumption 88.5 79.3 73.6Access Stability 95.7 88.8 84.2Nutrition Quality 69.8 57.9 57

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Sub-Section Sompov Kert Sam Nanh K’DowngLand Tenure 71.6 72 83Land Quality 83 78.5 68.9Crop Inputs 56.8 37.5 50.2Livestock/Aquaculture Inputs 49.8 19.6 40.8

Exposure and Resilience to Shocks Component:

- There is a large disparity in perceived recovery ability in K’Downg, having ranked as being overall the poorest village, perhaps this to do with its relatively outlying location.

- This, when taken into account along with the perceived higher level of exposure, is something to look into further.

- Overall, these scores are relatively low when compared with other components.

Sub-Section Sompov Kert Sam Nanh K’DowngDegree of Exposure 26.5 27.7 35.4Coping Ability 61.8 61.4 67Recovery Ability 58.2 48.5 36.3

Comments:

During the information sharing event, the K’Downg village chief was asked why he thinks that people are not as afraid of disastrous events as the other villages. His reply was that as none have happened in recent memory, the villagers believe they will not happen in the future. He also mentioned that people felt they would be well placed to deal with water and hygiene issues if a storm was to occur.

Non-Farm Assets Component:

- All three villages have medium to low scores in regards to employment skills and financial services, with the main disparity from this data set occurring in the Employment and Skills sub-section in Sompov Kert.

Sub-Section Sompov Kert Sam Nanh K’DowngEmployment and Skills 32.4 38.6 43.2Financial Services 55.2 46.2 42Fixed Assets and Remittances 64.9 60.8 63.5

The Issue of Migrating Adults – Findings Overview:

The second perspective that we adopted to analyse the data was by separating families that had one or more adults working outside of the household for more than 9 months in a year. We decided to do this

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as 43% of families have this migration background and it was a commonly cited issue during our early research, moreover the police chief mentioned that he believed around 1,000 people from the community had migrated in 2015. This yielded some of our most interesting findings, as it would be fair to assume that as these migrating adults do so to seek a higher wage to send back to their families, so these families would experience a higher quality of life when compared to those with no migrating adults. However, with one notable exception, this proved not to be the case. We will now outline some of the more significant findings in this respect, along with our ideas and possible explanations.

57%24%

19%

Number of Migrating Adults

0 1 2 or more

Figure 2 Pie Chart Showing Number of Adults Working Outside Their Household for More Than Nine Months per Year

The Issue of Migrating Adults – Findings Breakdown:

Fixed Assets and Remittances (Sub-Section of the Non-Farm Assets Component):

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- Families that did have adults living and working away, frequently in manufacturing or construction in Thailand, have a significantly higher fixed assets and remittances than those that didn’t.

- *scores based on questions about material possessions in the household, such as roof quality and televisions

Sompov Kert Sam Nanh K’Downg AverageAdults Away 76.8 74.3 76.6 75.9Adults at Home 51.5 55.7 51.1 52.8Score Differentiation +25.3 +18.6 +25.5 +23.1

Comments:

This makes sense, as a family that has an adult working elsewhere and making more money to send back should have more assets. However, this was the strongest difference in the category and suggests that perhaps the benefits of working away do not filter through and affect other areas of life as you might presume, rather luxury items (in the case of televisions) and home improvement (in the case of roofing material) are prioritized.

Land Quality (Sub-Section of the Farm Assets Component):

- Land quality is better for families with no adults working away.- *scores based on questions about gradient and type of soil of owned land

Sompov Kert Sam Nanh K’Downg AverageAdults Away 82.9 74 61.3 72.7Adults at Home 83.9 84.1 72.5 80.1Score Differentiation +1 +10.1 +11.2 +7.4

Comments:

This suggests that perhaps adults that move away are in part motivated by poor quality farming opportunities presented to them by their land, rather than just there are better wages on offer. Perhaps if land quality could be improved, people would be less tempted to move away.

Food and Nutrition Security Component:

- Families who had adults working away scored consistently lower over each of the three sub-sections of this component.

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- *scores based on questions about household eating less due to unavailability and family going to sleep hungry (consumption), experiencing a 2-week period in the last year with not enough food and experiencing a full day with no food in the last year (access stability) and a break-down of dietary habits (nutrition quality).

Sub-Section Sompov Kert Sam Nanh K’Downg AverageConsumption 86 90.6 80.4 81 73.4 73.8 80 81.8Score Differentiation +4.6 +0.6 +0.4 +1.8Access Stability 98 93.9 82.1 92.7 78 90.1 86 92.2Score Differentiation +4.1 +10.6 +12.1 +6.2Nutrition Quality 67.3 71.8 52.8 60.7 55.3 58.7 58.5 63.7Score Differentiation +4.5 +7.9 +3.4 +5.2

Comments:

This reinforces the point that despite being financially better off, the increase in financial resources does not necessarily mean that quality of life increases, even in as vital an area as food and nutrition.

Coping Ability (Exposure and Resilience to Shocks Sub-Section):

- Families with no adults working away scored higher in terms of their perceived Coping Ability if a disastrous event were to occur, such as a fire or drought.

- *scores based on questions about how long a household believes it would take to recover if one or two disastrous events occurred within a year, how long it would take to rebuild their home to a satisfactory standard and who would assist them if a disastrous event occurred.

Sompov Kert Sam Nanh K’Downg AverageAdults Away 60.2 56.4 61.9 59.5Adults at Home 63.2 63 72.3 66.1Score Differentiation +3 +6.6 +10.4 +6.6

Comments:

This is another example of a disadvantage of adults working away, with the problem caused by a reduction in the members of the family present to attempt to remedy the situation not balanced out by increased financial resources – this is another example of other areas of life in which it is detrimental to have adults working away.

Water Availability (Sub-Section of Domestic Water Supply Component):

- Families with no adults working away scored consistently and significantly higher in regards to the availability of water for their household.

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- *scores based on questions about how many months in a year a household deemed their water supply sufficient for their washing, drinking, cooking and cleaning needs, and how often they worried about this.

Sompov Kert Sam Nanh K’Downg AverageAdults Away 40.6 53.1 54.8 49.5Adults at Home 51.9 59.9 61.3 57.7Score Differentiation +11.3 +6.8 +6.5 +8.2

Comments:

This is yet another example of increased financial resources not permeating their way through to have any impact on a vital aspect of day-to-day life in Water Availability. That there is in fact such a significant score the other way suggests that not only are resources not utilized in this way, but that the absence of adults has a detrimental impact in itself.

Local Economic Environment Overview:

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Given the financial pressures many households are under, we attempted to gain a deeper understanding of the root causes of these pressures. We did this by analyzing some of the raw data from the survey questions relating to debt and borrowing and employment skills. Once again we adopted the perspective of comparing households with adults working away with those that do not, partly for consistently and partly to shed light on common economic coping strategies employed by households.

Debt and Borrowing Findings Breakdown:

Families with a migration background were shown to have an ability to borrow money more easily if needed than those that didn’t.

Almost three quarters of the 57% of the families with no adults away reported that it would be unlikely that they would be able to borrow money from financial institutions.

Slightly over half of the families surveyed reported that they owed a little amount of money to banks or money lenders, while 11% had no debts at all.

Nearly one third of the surveyed families owe their debts to relatives, 12% to private money lenders, 7% to microfinance institutions and 4% to village funds.

Figure 3 Debt and Borrowing Trends in Households with No Migration

These trends change in families who have one adult migrating each year.

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In one in four families, one family member migrates and in 19% of the cases, 2 or more adults live away from home.

A significantly higher number of families with a migration background reported to have easy access to money if they needed to borrow some (31%).

Despite this, 60% of all families assume they would not be able to borrow any money.

Surprisingly, 17% owe a moderate amount and 12 % a lot to banks in families with one family member abroad, which is considerably more than families with no background in migration.

The trend barely changes in families with two or more families abroad, even though it seems that slightly fewer families have no debt.

Households with migration background owe their money to village funds (16%), microfinance institutions (16%) and private money lenders.

Borrowing money from relatives and friends seems to be a less attractive option for households with a migration background than for households without this background, but instead households with migration background owe more money to banks and microfinance institutions.

Comments and Discussion:

Figure 4 Household Debt with One Migrant Member Figure 5 Household Debt with Two or More Migrant Members

Figure 6 Households with One Migrant Member Figure 7 Households with Two or More Migrant Members

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During our information sharing event the village and police chiefs raised comments in regards to the statistics shown above. According to the police chief, poor families with the aiming to migrate face very high costs, including passport fees and transport costs. In order to migrate, Khmer nationals have to go through a very costly application process managed by recruitment agencies. Most of these agencies are also located in Phnom Penh rather than rural areas. Hence, in order to be able to afford these costs, prospective migrants get loans from banks and microfinance institutions.

According to the International Labour Organisation, a prospective migrant worker is required to pay US$ 100 to an agency as an advance payment for processing documents, while the employer or recruitment agency internally lends US$ 600 (or about 20,000 baht) to the workers, which will later be deducted from their salary at a rate of around 2,000 baht per month during for 10 months. As the recruitment cost also includes profit and fee taken by agency, the actual amount of the loan should hypothetically be less than $600. With the loan repayment burden, migrant workers have to work longer hours in order to accumulate enough earnings for daily living and sending remittances home.

It seems reasonable then to assume that in the surveyed villages the debt burden for those with more of a migration background is larger than for families without. Due to the fact that villagers are more likely to come into contact with microfinance institutions and banks through the process of migration, debts are also increasingly owed to microfinance and banks, rather than village funds and relatives. Due to the high costs however, migrants struggle to pay back the loans and interest fees. As the police chief suggested, many migrants come back from Thailand feeling that they did not benefit from their work abroad as employers were either paying less than they had thought or the recruitment agencies requested unexpected additional fees.

As presented in the above survey results, families without a migration background are less likely to borrow money from microfinance institutions or banks in order to pay for future migration costs or day-day living costs. However, some poor families in the village of Sam Nanh reported that they usually ask relatives who are financially better-off to borrow money from the bank as they are more likely to receive loans. This corresponds with the results of the survey, which shows that families without a migration background mostly owe money to relatives. However, 58% of these households said they only owe a little bit. The majority of the debt burden could be owed by other households related to one family. Moreover, for some prospective migrants of poor families it is necessary to migrate in order to provide food for the family and education to their children. Another motivator for migration seems to be the ability to cope with disasters better, such as rebuilding homes after storms (despite this not being shown to be the case in the collected data).

The village commune chief also complained that every second migrant in the village migrates illegally. If the workers choose to work in Thailand through a smuggling network, they have to pay the carrier only around US$ 100 per person. Above all, this means that they do not have to wait for the administrative process to be completed before travelling to the destination country. Given the wide gap between the costs of legal and illegal recruitment, it is not surprising that many workers choose to migrate illegally. However, this may place them at risk of arrest and deportation. According to the police chief, the Cambodian government tries to communicate with the government of Thailand to send back any illegal Khmer labour workers. This is also

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because Khmer labourers migrating abroad illegally have zero social protection in terms of security of wage, labour rights, sexual harassment etc.

Considering the results of the survey it seems very important to prepare prospective migrants better before their departure. Currently there is not systematic pre-departure training for migrant workers in Cambodia. Only a few NGO’s and recruitment agencies provide pre-departure training on health, human rights etc.

As remittances seem to be invested in fixed assets, (such as televisions) rather than consumption and improved nutrition, prospective migrants should receive training in financial literacy and ways they might invest their money better. The police chief of Phnom Sompov complained about the fact that some people come back with no money as they did not manage to build any savings. Rather than spending money thoughtfully, with a longer-lasting impact for the family, it is spent on leisure goods and alcohol. Thus, recipients use the capital to maximize leisure rather than work to maximize utility. Therefore, we propose that helping prospective migrants to choose from the options available, e.g. providing information on available bank accounts, savings accounts, costs and loans, cheap bank accounts to transfer money from Thailand back to their families etc. it might encourage families to make livelihood and financial decisions more wisely.

Migration and Employment Skills:

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The analysis of the questionnaires reveals that families with a migration background are more likely to run or manage their own agricultural business or provide skilled services than families with no migrant member.

During the last 12 months, has anyone in your household managed or run their own non-agricultural business?

Only 30% of families with no migration background have engaged in any business related activity in the last 12 months, whether that be for 1 month or up to 7 months or more.

In families with one family member working away, almost 50% of households have run or managed a business, while two thirds of households with 2 or more adults working away run or manage a business.

Additionally, families with a migration background seem to run their business for longer than 7 months; for instance, 35% of households with family members living abroad run or manage a business.

Comments and Discussion:

Even though the police chief complained about the fact that migrants return to their families in the villages with no saved money and accrued debt, there are many cases in which the family was able to save and then build or run a business besides their agricultural businesses.

This is a positive sign, suggesting that a decent amount of households with a migration background have received pre-departure training and are aware of the possible benefits that migration can have if the remittance money is spent and invested sensibly and efficiently.

Providing skilled services in Banan Province does not seem to be an attractive option however. This is despite families with a migration background seeming to at least offer skilled services a few times, or every day.

Additionally, there could be no relationship found between migration and any skilled services that households offer beside their agricultural businesses.

Roughly 80% of households in Banan Province have not offered any skilled services in the last 12 months, with or without migrant family members.

Potential Avenues for Further Research:

It was difficult to try to incorporate the Sanitation and Hygiene Component, due to a lack of immediately obvious impacts either on or from other Components. Potentially however a link

Figure 9 - One Adult Migrating Figure 10 - Two or More Adults MigratingFigure 8 - No Adults Migrating

60%

3%5%

1%

21%

10%No Adults Migrating

NoYes, 1-2 monthsYes, 3-4 monthsYes, 5-6 monthsYes, 7+monthsdon’t know

44%

6%13%6%

22%

9%One Adult Migrating

NoYes, 1-2 monthsYes, 3-4 monthsYes, 5-6 monthsYes, 7+monthsdon’t know

23%

19%

8%4%

35%

12%Two Adults Migrating

NoYes, 1-2 monthsYes, 3-4 monthsYes, 5-6 monthsYes, 7+monthsdon’t know

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could perhaps be made with the Domestic Water Supply Component, subject to further research.

Although started, a more in-depth analysis could be made of any existing relationship between each village and the number of adults working away or at home. This may give another perspective on the reasons for adults seeking employment elsewhere.

One idea we had that was not followed through due to time constraints was to establish a relative poverty line, e.g. those with a score under 30 in the Domestic Water Supply Component. This would require careful analysis of each score from each household relative to one another, but would prove extremely useful in identifying not only the most vulnerable households in the community, but also which aspects of day-to-day life should be focused on in the future.

In future surveying exercises or focus groups it would be interesting to try to gauge which Component each household feel needs most urgently addressing; although an estimate can be made from the scores from each Component comparatively, this is not certain and would be invaluable in establishing which areas should be targeted in future cycles.

An extension of the adult migration analysis would be to conduct a further breakdown of how many adults each family has working away relative to the size of the family. This would give an idea of whether there is an optimum number of adults working elsewhere that benefits the family, dependent on the make-up and size of the family.

Further research into the structure and type of existing family agricultural businesses would potentially provide an insight into which of these is most effective and beneficial to the family.

A more detailed picture of the kinds of debt owed by households in terms of payment schedules, interest rates, why the debt has been accrued and general etiquette if informally owed would be useful in understanding the economic ecosystem of the community and consequently which types of livelihoods initiatives they would be most receptive to.

If a more detailed understanding of coping and recovery techniques specific to each different kind of disastrous event could be developed, this would enable more effective mitigation and adaptation initiatives, as well as the most useful strategy to adopt in terms of pre-emptive resilience building.

Try to establish whether there are literacy or financial training opportunities or saving account schemes offered by NGO’s or local organisations for prospective migrants in Banan.

The issue of fish-farming and the difficulties associated was brought up during the information sharing event – this was the first we had heard of it being practiced and could provide an alternative focus for future projects alongside traditional agriculture.

Finally, a physical map of households so far interviewed would have been incredibly useful in order to get an idea of common issues that could be explained by geographical location, and should be considered when next conducting surveys. Moreover, this could be developed into a skill exchange initiative if professions and personal capacities were also mapped, facilitating community linkages and allowing households to work more closely together to address their own issues.

Criticisms of the Process and Points for Improvement:

Due to a password protection we were unable to see the exact formulas used to produce the scores out of 100. Being able to access this would have deepened our understanding of the data

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we collected, one example being how the Nutrition Quality Sub-Section was calculated (certain foods that may have generated a high score might not be prevalent in the context of a rural Cambodian community). This would have given more credibility to our analysis and findings as well as ideas for future research techniques.

Whether by design of the questions (e.g. questions 30 and 31) or a lack of understanding on the part of the interviewers, we received a large proportion of zero data values, undermining the representativeness of our data. Either way, if the same survey is used again, extra time should be dedicated to developing a clear understanding of the questions and what they are designed to find out.

Conclusion:

We hope that this report has provided an insight into the needs of the community of Banan and can therefore act as a foundation to ensure that future cycles of volunteers arrive informed and ready to

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effectively contribute to resident’s day-to-day lives. It quickly became apparent that not only was an agricultural youth co-operative not in keeping with the ambitions of local youth, but that it had been presumptuous and limiting to assume that it was. In addition, the model of the existing adult agricultural co-operative is not transferable due to it’s financial structuring, and future initiatives to engage the youth should be developed independently, taking into account their circumstances and basing the project focus closely on their ideas; we believe that interactive consultation events would be an effective tool to achieve this in the future. In addition, it needs to be accepted that migration in search of better pay is an established facet of community life and rather than attempting to change this, education and preparedness on this issue should be prioritised. With this acceptance, the impact that migration has on the affected families can be better understood and therefore addressed. Lastly, we believe that there is a willingness among both key community stakeholders and local residents to work in partnership with VSO ICS volunteers in the future, but the direction must come from perceptive, careful research and effective working partnerships that effectively utilize existing capacities and allow residents to become agents of their own change.