Of Molehills & Mountains

d Of Molehills and Mountains The Tiers & Tears of Research Enumeration Exploring Methodology in Micro Research

Variables in Survey Enumeration:

Poverty? or Ingenuity? These photographs show dwellings erected out of driftwood and other materials on a beach in Northern Samar, Philippines, after the typhoon season a .

(This document represents the views of the author only.) From the start of any research project in a developing country, an enumerator is faced with a dilemma: With the staggering number of variables and consequences, comes the question, where do I start in this lot? The work of an enumerator is to collect and enumerate raw information and present these in raw form prior to any analysis. Although some analysis is always required, it is normally the role of an end user’s programme analyst or statistician to interpret the information. Giving in to the tendency to analyse information during a canvassing period is contrary to obtaining an unbiased result. Also, the end user or the organisation/agency commissioning the research may be far removed from the research site, may be making judgements from out of date or manipulated macro information, or may have biases that are restrictive to an enumerator. It is often assumed that ‘one size fits all’ and many projects flounder and large amounts of monies are lost because local or micro research was not undertaken, or that assumptions were made from un-validated information. The enumerator’s first task is to guard against assumptions that may colour the results of his research. The Investors in Relief or Development Projects: The presentation of enumeration ‘ways and means’ documents and the conclusions reached from the enumeration are numerous and in context, vary widely and it is often in the presentation that interested readers’ perceptions are formed. Keeping in mind that an end user (be it academic or organisational) has financed a research project, many report documents are deliberately couched in terms that do not affront an end user and these can lose credibility in the eyes of knowledgeable readers. Research documents that openly (albeit inoffensively) point out to an end user that the end user lacks the ability to provide a full response to a given situation, are taken as honest appraisals and viewed by readers with respect. In other documents, we see where a researcher has openly stated that the original parameters of a research project totally failed to encompass the need at the micro level and that there was a need to carry out secondary enumeration that did reflect the situation. These, however rare, also gain credibility insomuch that the researchers

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could not provide an adequate representation of a situation, as the tools provided were unsuitable at micro level. This tends to show up the corporate thinking within many national and international organisations and agencies, as pointed out in “Uncertainty on a Himalayan Scale” (Thompson, Warburton & Hatley 1986) when they state that “In such homogeneous settings the chances are that everyone will see the problem in much the same way (if only because anyone who does not soon finds himself in (on) the outside of the organisation).” As with industry, the ‘corporate image’ does not take challenge kindly. Corporate ‘imaging’ has now crept into some of the development organisations, with logos and identities to not only attract potential donors but also to streamline their response criteria. “Child Friendly” is an example of how far some of these organisations have moved away from the intellectual backpacker image to the corporate offices, corporate livery, stock market investments and subsidiary companies, although still dependent on ‘mom and pop’ donations. Add in the jargon laden international consultancy firms, again with corporate images, and we see a vast industry that feeds upon itself. As a resource speaker, I once attended a workshop, facilitated by an international consultancy company that had a six-month contract with an end user. When asked privately regarding the conclusions he expected to arrive at, the lead facilitator boldly stated that he already knew what the conclusion would be; he had decided this from previous consultative meetings and it was now a matter only of guiding the participants in the direction envisaged by the consultant group. Development agencies invest very large amounts of capital to relieve a known situation, expecting to gain some benefit from this investment. That large amounts of this capital investment are used to administer projects, can no longer be supported, as capital inputs from donors does not keep pace with the world’s social problems. In the words of one development organiser, “The cake is the same size, but it has to be used to feed more people.” To be misguided by poor or incomplete data or assumptions made from macro information, wastes vast amounts of resources. Investment made in primary or secondary research is never wasted, whether or not the results reinforce or weaken the investor’s thinking. One illusion that should be challenged is in the table in the documentation of Michael Ward in “Social Research in Developing Countries – Missing the Point”, that the data collection techniques either have to be “unstructured/flexible” in ‘qualitative’ research or “structured/rigid” in ‘quantitative’ research. I believe that this cannot be supported. Structured or rigidly conducted research in developing countries is often over-controlled, biased and more dependent on protocol than common sense. Experience has shown that a rigid discipline in preparing any research project and adherence to a strict means of recording raw data in the field, and flexibility in data collection are not incompatible. Strict formality of format with an informal means of gathering can work extremely well. As nearly every researcher will confirm, national and international macro statistics are often out of date, incomplete or manipulated by those who have an interest in portraying the situation in a certain way. The information is also often required to fit the end user’s

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ability to respond. Thus, the research enumeration and analysis may show incidences where the end user does not have sufficient technical resources available to be able to respond to the full need. However, the recording of partial or total inability to respond should be recorded with equal importance, since micro situations often do not fit macro assumptions. However, macro level documentation is usually the starting point of any micro level research, used to prime a format for a micro investigation. National and international agencies and organisations independently produce documentation to show that certain areas [macro] of the world are under stress in terms of poverty. There are sufficient statistics available to show that within the macro are distinct areas [sub-macro] where particular stresses are highlighted. These may be environmental problems, conflicts, poverty, political, religious, or a combination. By definition, there are variables at the macro and sub-macro levels that can only be explored and quantified at the super-micro, micro or sub-micro levels. By definition, sub levels of macro or micro situations are lead variables. The author finds some difficulty in jumping between macro and micro without a safety net and, for the purpose of this document. The terms macro and micro are used as points of enumeration entry and further sub-divisions have been made to enable greater clarity. The following are terms that may be found within this document.

Macro Sub-Macro Super-Micro

Micro Sub-Micro Few organisations carry out research only for the sake of research. Usually, information is required (A) to support or challenge an end user’s line of reasoning that certain areas should be designated areas (focus areas) for involvement in relief, development or monitoring, (B) to be able to provide primary profiles of these areas at micro level in order to be able to determine the type and amount of financial and human resources for involvement in these areas, (C) to establish a source of primary baseline data for the potential assignment of available resources, or (D) to provide a source of primary baseline data for future monitoring purposes. Priming the Process: Once a decision is made regarding an area or situation in stress, it becomes necessary to format a means of gathering the required ‘core set’ of information in order to respond to the end users need to plan a response to the given stress. The term ‘core set’ is used to define the very basic information required, in order to formulate a minimum response to the stress situation. In formatting any data collection hardware for a survey, the question is raised: “What are the basics that the end user needs to know about these communities, to aid them in decision making for involvement in aiding reduction of the stress factor?” 3

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Also, given that most national and international information available is macro, giving the impression that ‘one size fits all’, the canvassing needs to be carried out in community ‘types’ to better determine the differentials that may have an on influence the relief or development needs. This type of survey would reflect common points that would be of use to the end user in terms of the financial and human resources required to meet the need. As an example, the lifestyle of a coastal community cannot be compared with the lifestyle of an inland delta or upland community, although they may not be separated by large distances. They may use the same fresh produce market and have access to the same local government amenities, and yet many factors of their lifestyles could differ. The variables to be found in attempting to include these individual communities in a common research project are infinite. Within this survey, three individual sub surveys were in effect carried out, thus providing an overall comparison as an added factor of research project results. Too many surveys rely on household or environmental activities or assets only, omitting community profiling that is important to determine the ‘community management’ capability that more often than not has a significant influence on the economics of the household or status of the environment. Yet, it is not possible, or safe, to include all information on one enumeration questionnaire. From this, it can be determined that two distinctive sets of information can be gathered in each community type during a visit: A community profile and individual household or environmental statistics. The poverty status of households often depends on the overall management of a community by its democratic or dynastic leaders, and the service provision within a community can often determine the community’s ranking within a wider area. Implementing the Process: For large scale information gathering exercises, there are two definite requirements: (A) to gather the overall information as required by the end user and (B) to put together the technical aspects that make up the core statistics. The task of enumerating the data requires the expertise of a professional researcher, who possesses the discipline to adhere to the rigid requirement of data gathering. This researcher’s expertise is gathering data and he/she may not have the benefit of the technical know-how to be able to interpret certain information. In this case technical advice is required, be it on a single issue or multiple issues. Categorising or ‘typing’ the communities has great importance and should be of paramount consideration before the onset of any survey activity. In the instance of natural resources livelihood dependency or in an environmental stressed area, this is critical to any research analysis. Basic information should be available to assist in these considerations. Varying altitudes affect natural resources livelihoods and environmental issues, and although there may be common factors, imprecise results can be misleading to a non-technical enumerator. In the case of small-scale research projects, it is often sufficient to use an enumerator with the technical know-how, primarily advised by an expert in data gathering. To gather information, the lead enumerator should determine that, although the formal formatting of the survey must be strictly adhered to, the means of canvassing might need

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to be informal, in order to avoid the formal structure whereby the hierarchical or authoritative structure would dominate the canvassing process, making the respondents provide information that they think the canvassers want to hear. An informal approach would also decrease the likelihood of enumeration fatigue. All researchers make a difficult choice prior to the start of the canvassing phase: they have to decide whether to use any previous local statistical documentation. Previously gathered information may influence the direction of the survey; any bias should be avoided. On completion of the survey, findings could be compared with existing documentation as an exercise to weigh new findings against any other sources. Familiarising enumerators with an area is acceptable, as in ‘this area is a major wheat producing area’, not ‘this area is a major wheat producing area that producers yields of x tonnes per hectare and yet has high child malnutrition …………’. These details will compromise a research project and may bias enumerators into making assumptions that have no meaning. The formatting of a questionnaire should not be carried out in the area that is to be researched, as there are likely to be alterations in questions that should be asked. Once an official research project has begun, the format cannot be changed. Formatting should take place in the form of a pilot survey in an area outside of the intended research area, but similar to it in situation. In this way, important variables can be noted and included in the research area questionnaires. At Grass Roots: Like all visitors to a community, survey enumerators attract a lot of attention and most community members are eager to participate. This can be both an advantage and a disadvantage. Groups gather around enumerators and it can be tempting to have as many questionnaires as possible filled from a single group. It will be soon realised that the responses become similar and that respondents are copycatting. In public, many would wish to give the impression that they fitted into the group and would, at times, become economical with the truth in order to tailor their responses to fit the general drift. From this, we should quickly learn that an enumerator can use a maximum of two respondents in any group before moving on. This is where ‘capturing’ respondents in their households has value, as they are less likely to be able to tailor their responses, not having heard any of the other responses. However, in community profiling, group responses can be useful. In most cases, more than 50% of the households should be canvassed, and in cases where there are fewer households than questionnaires, all can be canvassed. In large communities, the canvassing can be carried out in sub-units (sub-macro) that fit the general focus of the survey. In any survey, incidental information is proffered and, although this is not usable in a formal system of data gathering, it has value by helping to ‘fill out’ formal statistics. Thus, we will come up with two sets of core data [community and households or environment] that are strictly gathered, albeit in an informal manner, as well as supporting information that will be part of a research project tour report. Once the questionnaire is set, no

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changes should be made apart from slight changes in the presentation of the questionnaire. The incidental information that is noted has great value, as this often reflects community or individual free thinking, and, if presented correctly, can greatly aid the end user in the decision making process. Too often, research projects are dehumanised and clinically implemented at field level; this clinical approach is often responded to with overt hostility towards the enumerators. The temptation is to get in and get out as rapidly as possible, but to do so is a mistake. Time taken is wasted, time given is profitable. Worst of all, enumerator fatigue can have an affect on the outcome of any field level research project. Keeping a human perspective will reduce this unwanted risk. Thus, the informal approach [or qualitative in the terms of Michael Ward’s research criteria] has value. Meetings with community leaders or elders are often accompanied by food and drinks, and although this may seem to take up a lot of the enumerator’s time, it is probable that the time given may shorten the time needed for household data enumeration. Time given is profitable. It may not be necessary to spend large amounts of time in an area, as asserted by N. S. Jodha in “Social Science Research on Rural Change: Some Gaps” in the book edited by Pranab Bardhan in "Conversations Between Economists and Anthropologists" (1989). A question to be raised here, where the enumerator/s had an almost permanent presence, over a number of years, is to ask what affect the almost permanent presence of an enumerator had on the outcome of a community’s development. Is the intervention itself significant on the community’s development At meetings with community leaders, many issues are raised that have no direct relationship with the data research project. These should be noted as incidental information for inclusion in a tour report. These may include health and nutrition matters, seasonal income generation opportunities and problems, general production levels, women’s issues, youth issues, development priorities, co-operation of the local government executives, etc. At no time, should national elections or politics be raised. Variables within Variables: Within any community, there are factions (social groups) that have their own lifestyles and possibly their own agendas, be they castes or special interest groups. Community lifestyle is usually good where those who are responsible for the management of the community can pull these groups together and where there are reasonable community services provision (health, education, potable water etc). Service provision is often the key to a community’s poverty and development status. Although not the only basis for conclusion, as there are many variables, we often found that the least impoverished communities were those that had a higher level of service provision and visa versa. Politics can have a role in this, as investment in services from a higher authority is often dependent on the voting power and persuasion of the community leaders. Knowledge of the local language can prove important. In some communities, we noticed that householders had dug holes in which to put their trash, whilst in other communities, the trash was just thrown onto heaps. We wanted to ask about this. Since the translator did

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not (or would not, given the outcome) comprehend the word ‘hole’, ‘hole’ is the word that we used during interviews, with many hand gesticulations. This was always responded to with mirth from the ladies present, and we later realised that they thought we were asking about testicles, as the local word for this sounded very much like the word hole. We dropped this line of enquiry as a result. Whilst in an area, local market surveys can be commissioned for a ‘basket’ of food and these can show the market forces, both for natural resources produce and for commodities. These can have added value, as they may show one or more variables that affect separate communities. Communities ‘A’ and ‘B’ may have similar income sources and levels, yet community ‘A’ may have the capability to produce more fresh vegetables and thus their basket of food items will cost less than community ‘B’ where fresh vegetables have to be imported, showing a disparity in household expenditure on basic foods. Habituation to Enumerators: Out of interest (in India and Bangladesh) we looked at the number of times certain communities had been put under the microscope and much to our worst expectations we found that those communities with easy access for vehicles had been subject to researches many times, that those with reasonable access had been moderately researched, whilst those with poor access had been rarely or never researched. From this, it would seem that enumerator comfort, including speed of progression, is a factor that is given too much importance. Furthermore, the communities that had been subjected to many surveys, had realised the potential for development benefits to their community and subsequently focused their responses on issues that were of most concern to them, overestimating the problems to gain sympathy. Any information from these must be considered corrupt. Unfortunately, the findings from this incidental survey were never officially recorded and thus, not presentable. However, they show that caution should be taken when the selection of communities is in hand. It also shows that enumerators should be prepared to travel in less comfort to reach the less accessible communities. There is no right way: In chapter 2 of "Poverty, class and gender in rural Africa" (1990), the authors take the brave step to criticize the methodology used by a number of previous researchers but totally fail to make their case, despite valid points raised. To produce an unbalanced criticism of previous methods used at different times, ranging from the 1950’s to the 1980’s, is at best foolhardy and at worst crass, especially in the light of vastly improved hardware and support services available in the 1990’s. To describe the "shortcomings" and "problems" of previous methods could be supported if the authors had not gone on to give the impression that theirs was, in the 1990’s, the only ‘right’ way. This is naïve, particularly when they go on to state "The methodology adopted for the fieldwork in the West Usambaras could not escape entirely from the limitations arising from a time-specific snapshot." But why should it? Nothing had to be "adopted" if the breaking of any moulds or 7

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challenges to any methods is to be undertaken. There is no need to attempt to trample over other methods from previous times to gain notoriety when the parameters have changed so much and decades have passed. The point of academe is to challenge the boundaries of the fields of research, but to claim a new method that is actually adopted from previous methods, while trashing those same methods, leads to a total loss of credibility. There is no ‘one right 1 way’ in research. In terms of publishing, lengthy ‘end notes’ only serve to confuse and cause much shuffling through pages. Succinct 2 ‘footnotes’ provide adequate guidance. In any survey, there are many variables that come to light. It would take academics, anthropologists and development experts many years to follow all of these through. In addition, many different, even conflicting, conclusions would probably be reached. The old adage that asking ten experts to give a conclusion will result in eleven or more documents has a certain truth about it. The object of any survey is to provide the end user with one of the many tools needed to determine its next strategical move as a relief or development agency, whether or not they are resident in the area. Relief and development agencies’ resources are finite and have to be used in the most effective way within a given area, situation or mandate. A survey is part of a process and, as such, proffers the most basic and up to date information available regarding only a limited set of variables. To seek to cover all variables would entail a process that would take many years. End users provide a timeframe, within which to generate results, and sufficient funds to enable the research to be undertaken. Should the end user require additional information to aid planning and implementation, it is often the supporting or incidental information that provides sufficient guidance and also may explain many of the variables. It might be found that a variable may, in fact, have a significant impact on the overall status of a community although this was not known prior to the enumeration. An example of this might be the influence that a seasonal weather pattern may have on the cost of fresh market produce or work opportunities. The correlation of information can show significant consequences on whole communities, in as much that malnutrition, expenditure on health remedies, loan repayments etc., are considerably affected by these variables.

The Variables: The dictionary defines ‘variable’ as “A quantity that may take on any set of values.” Time factors and costs are a major restraint to any field research, as end users have budgets and deadlines to meet. Often, the fact-finding tours are a necessary evil to be endured and they want these completed in the shortest available time. This puts the enumerators at a considerable disadvantage, as shortcuts may have to be taken. Who, in the space of a single document or time allotment, could describe all of the variables and inter-related consequences attached to them? Some of course are obvious 1 2

Right: as in correct, accurate, true or precise. Succinct: as in brief, concise or to the point. 8

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while others only emerge in the course of the research. Who, for example, would think that soil erosion in upland and mountain areas would have any connection with fish catches? Yet the research has found that this is so. Who could imagine that the illegal logging activities in some areas would have a direct affect on urban migration? Yet this also is so. At macro level, it is often assumed that man is solely responsible for the destruction of coral reefs. However, the fact is that El Nino probably destroys more living reefs than man ever could. Also, soil erosion has a disastrous affect on reefs, clogging these with silts and acid minerals washed down to the inland coastal waters. To qualify in a research project, a variable should have a direct bearing or consequence on the information being enumerated. Prior knowledge of variables is of great assistance at a future phase of any project. However, no enumerator can be expected to be able to detail all variables, especially without technical knowledge, and it is usually not until a relief or development project is started that many come to light. At macro level, it can seem that effect ‘A’ is created by visible cause ‘B’ and that the means to correct the situation is to address problem ‘B’. At field level, the researcher may find that although problem ‘B’ is the visible cause, there are variables attached to that cause that have a strong bearing on the level of effect ‘A’ and that primary concentration should be given to these variables to reduce the problem.

Affect ‘A’

Visible Cause ‘B’

Direct Relationship Indirect relationship Indirect relationship Indirect relationship

Cattle diseases such as Foot and Mouth Disease appear in cycles [five to seven year cycles, as near as can be judged]. These cycles are often ignored or not known about at field level. Were these known and acted upon, considerable savings could have been made. This knowledge could persuade livestock field workers to change from reactive veterinary practices to proactive practices. The variable here is the unused ‘knowledge’ of a cyclical disease pattern. Often, variables are influences by cultural beliefs and practices that are resistant to change. For example, women in some cultures do not bathe during menstruation, despite modern amenities and access to information regarding modern hygienic practices. The explanation behind the (non) practice has long been forgotten, yet the practice persists. Measuring quantities and areas, and translating these into readable information in research documents, has always been a nightmare for researchers. As yet, no standard formula has been adopted and it is unlikely that one could be formatted at all. Where the West uses understandable standard measures, many communities in developing countries

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still retain their own measurement systems. A tin of rice, a sack of sweet potatoes or a cartload of manure, etc. For example, a researcher may ask a local “How far is it to the next village?” and be told that it’s just a little down the road, only to find that it’s 10 kilometres or more away. Distance, in many of these cases, is measured by the time used. It would have been better to ask not how far, but how long it will take to get there. However, time is also relative. Since villagers had time at their disposable, 10 kilometres is considered a ‘little way’. The author remembers once, researching remote communities in Africa and using a rugged motorcycle to save time, being taken on a shortcut of 12 kilometres that took some 45 minutes, when the ‘long way round’ was 16 kilometres and took less than twenty minutes. In this case, the concept of both time and distance are irrelevant to the community, as their community was difficult to reach by any means, other than by rugged motorcycle, or by foot. The annual weather cycles should always be taken into account as these have direct effects on agriculture, construction, fishing, the general incomes of blue-collar communities, health and even education. From the seasonal weather pattern comes a work opportunity model that, when correlated with prices in the local market, provides a monthly spending power indicator. Many NGOs have considerable problems with loan repayments at certain times of the year and a spending power indicator will show that seasonal factors can reduce the ability to repay loan instalments. When correlated with malnutrition in certain communities, the seasonal work opportunity model and the spending power indicator can show why these communities suffer.

Marginalisation: This term ‘marginal’ is frequently used in conversations or documents to refer to situations that are unclear by the researcher’s standards. Between the poor and the rich we see marginal peoples; we see land classified as marginal and often hear of marginal voters. From these examples, we may imply that the voters who are neither rich nor poor are sitting on a fence in the middle of a field that has neither good nor poor soil. In poverty terms, marginal people are those that, at the present time, are a little better off than the impoverished but are likely to slip into the impoverished category if a situation worsens. In this case, the word marginal cannot apply to voters who have a choice to make. Therefore, we have two meanings for the word marginal and perhaps it is time, for the sake of clarity, to utilise another word to describe the fence sitters, and reserve ‘marginal’ for those that are on the verge or periphery. Perhaps we should formally label the fence sitters with choice as the ‘ambivalent’.

Social Preferences [or indifferences] in Community Scanning: Personal Choices: In many published research papers, the facts are often presented as ‘hard facts’ and do not take into account the social preferences or personal choices made by community

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members. Too often, the structure of a dwelling is used as a poverty indicator; where there are natural materials used for dwellings, households are usually assumed to be poorer than those that use ‘modern’ materials. Researchers ignore the social preference of the occupants who may think that natural materials are more comfortable than modern materials. There is no doubt that dwelling construction is a poverty indicator but not an absolute indicator. In education, it is often assumed that the high dropout rate of children in the first year of education is due to poverty. This is not always so, as there are other variables that may trigger dropouts. Many children, for example, stay at home because they find school very boring; it is more interesting to stay at home to help mum or dad. The assumption is made that because these children are seen to be working, they do so because of poverty. What people sometimes fail to consider is, although may be from low-income families, they may be working because they find it more interesting than being at school. These are variables that have nothing to do with poverty but are a social preference or social concerns. Parents themselves, mostly poorly educated, may say that it is okay if their child does not wish to attend school. This could be called social indifference. The decision to drop out may also have been caused by doubts regarding the aptitude of teachers, in which case, interventions to improve teacher training may be more effective than anti-poverty activities. In many instances, it may be necessary to break the habituation to existing circumstances, as this does not allow ‘thinking out of the box’. In documentation [Beyond the Visions and Missions of Development in Northern Samar (Philippines) VSO ⊕ / PDI ⊗ 2006] the author used statistics from a 2003 community and household survey [Project 813] and correlated the results of this with the provincial government’s database information, the Department of Agriculture statistics and the National Statistics Office 2002 Agricultural Census. The final document also included market price statistics, weather and other statistics. Although the VSO survey showed many instances where the VSO enumerated information aligned with the other information available, there were instances where variances were found. Further research showed that those responsible for this information had not updated their information from physical research or had used old information and manipulated these. There were other instances when deeper investigation of the local government information clearly showed that one mathematical formula had been carried over to all of the individual municipalities. The end result was a totally false representation of actual statistics. Visits to communities revealed that no local government enumerator had been seen in the area for many years. The author of the VSO/PDI document had to spend many months validating as much local government information as was possible, prior to including these in the documentation.

⊕ ⊗

VSO = Voluntary Service Overseas PDI = Project Development Institute 11

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As many authors on research methodology have noted, the use of electoral rolls, consumer and other lists for sampling immediately introduces biases in any research project. For example, the 1973 survey of smallholder tea producers in Tanzania [Sheila Smith 1990] produced a list of names that included names of family members who had no ownership rights or participation in tea production. This was because the names were given at the behest of others, to avoid acreage limits on tea garden ownership. Many have used electricity consumer lists as guides, overlooking that these are comprised mostly of people in urban areas, where electrical supply is the norm, whilst there are large areas of nonurban communities, where electricity is perhaps still a thing of the future. In addition, electricity consumer lists may not even accurately reflect the number of people with electrical connections. It has also been found that official records show that (say) 40% of dwellings have connections, whereas physical research shows that (say) 85% of dwellings receive electricity. Many of the unofficial connections buy electricity from their neighbours, avoiding the need of official meters. When most communities were originally established, common sense dictated that these communities settle near a source of safe drinking water, and modern records still report these as being sources of potable water. However, there are many cases where the size of the community has outgrown the sustainable supply of water, or that the water supply is adequate but no longer ‘safe’ to drink. There is now a requirement to make a distinction regarding whether or not the once potable water is still safe. Prime water sources are now, in many cases, polluted and no longer potable. Other variables show that spring water sources have diverted due to natural causes and whole communities have been left dry. Maps that we often have to refer to can be fifty years old or more. Very few local people have ever seen a map and cannot relate a flat piece of paper to their environment, the usefulness of maps may be limited. However, studies in India and other countries have shown the remarkable accuracy with which the local people can create a three dimensional map out of soil and pieces of wood. We learn from the communities as much, we hope, as they learn from us, and this is especially so when development advisors are assigned to a project at grass roots level. Reading the Numerations: An investigation into the number of malnourished schoolchildren showed that the root cause was directly related to the work opportunities available and these, in turn, dependent upon seasonal weather changes.

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100%

95%

Work Opportunity Trendline

90%

85%

Northern Samar, Philippines Low-Income Household Work Opportunity Monitoring

80%

75%

70% Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

An end user was interested to look at a particular region and discern why certain communities had increasing amounts of household debt. They suspected that declining rice yields was the cause. As it turned out, they were correct in their thinking, yet there were many variables that took control out of the householders’ hands. The result of the investigation showed that although the low crop yields were the primary cause, there were many unavoidable variables, with consequences, that required attention. Not least of these was the need to neutralise the soil condition and assist with soil erosion defences in the upland areas. Many rice production areas depend on heavy rainfall and, to some extent, flooding. Yet one of the major problems often found is that, during monsoons, there is too much water. Few communities have put up storm-water dispersal systems. Great effort has been made to entrap water to ensure sufficient water-logging for cultivating and planting, yet this same system is often the cause of excessive flooding and crop loss. In this instance, the only activity that these community members could have undertaken was to have improved the storm water drainage prior to the monsoon season. 13

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The roll over affect from this single problem causes subsequent cultivating and planting delays over a number of cropping seasons. As an example, the following chart shows an actual situation of illegal logging being carried out on one island in the Philippines. The extract is taken from a document entitled "The Domino Effect", commenting on the consequences of one action upon another within a community, in which the main source of income for rebels came from the illegal logging activities.

The chart poses some questions regarding cause and effect. Does this depict the cycle and are the armed forces correct in their assumption that rebels are at the beginning of this cycle? Or, are the rebels a result of the lack of social services and of environmental depletion? Of Molehills and Mountains: As can be classically seen from the excellent analysis in “Uncertainty on a Himalayan Scale” (Thompson, Warburton & Hatley 1986), it is not possible to define what form a molehill may take at any given time. Indeed, molehills at the foot of a mountain are unseen, much less noticed, by those that sit atop the lofty peaks. The comprehension of many an end user is often one that suits the end user’s ability to respond. Thus, any knowledge gained should fit their parameters. Too often, end users find that the knowledge gained

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fits only where it touches and thus inappropriate claims are made to be able to respond to the whole need, whereas, in fact, the end user may only be able to respond to a small percentage of the whole. The corporate status seems to be from the ownership of the knowledge and not the ownership of the responsibility. It is simply not possible to identify a micro situation from a macro overview, although an end users macro viewpoint is the prime motivation of preliminary response. It also shows us that not only do we need assistance in the navigation of these lofty heights; we also need assistance to navigate through the mass of molehills, or even to identify variables on, in and around the molehills. Those that dare to challenge the forgone conclusions made at macro level may be seen as pariahs by some, and yet are seen as guardians of the moral right by others. Until we, who work in the field, stoically plodding through the maze of incidentals that make up micro research, decide to stand with the pariahs, we too shall be lost amid the plethora of small details. That we need scientific information is a given; otherwise how will we be able to judge if we are involved in assisting forward motion or maintaining stagnancy. The challenge, as stated in “Uncertainty on a Himalayan Scale”, is whether to face mountain "bald as a coot, or buried under a pile of biomass”. We dramatically alter the lifestyles at micro level and alienate individual communities when we lump them together as one entity. Research documents provide historical information, although these often out of date by the time of publishing. None the less, these are extremely important documents that, if validated, should not be taken lightly. We all need starting points. We can also be tempted to go off at tangents, but if the tangent (variable) is interesting enough, there is cause to include this in documentation. Never has there been or ever will be one ‘right way’ to collect micro level statistics, although there are many wrong ways. And like fleas on a dog’s back, variables are numerous but not always seen. Core Studies-2006

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Understanding [or otherwise] some of terminology in humanitarian projects used in this document: Community profile:

Community management: Community typing:

Core set of data: End user: Incidental data: Informal data: Intervention: Involvement: Lifestyle:

Macro: - - Sub-macro: Marginal:

- - Super-micro Micro: - - Sub-micro:

This is the result of research and enumeration of community statistics, the management capability of the community leaders and the service provision within a community, whereby management decisions affect individual community members whether or not individual community members have a participatory role in any immediate decision taken on their behalf. Whether official or not, all communities have some form of hierarchy, be it through tribal elders that lead through family ties and have guided a community for many generations, or through regularly elected officials. All communities are managed, in one way or another. All communities have an identity and, in enumeration analysis, it is important to use these identities as a means of comparing lifestyles. Communities within a given area may vary in livelihood dependency and it is of great importance that these are identified or ‘typed’. Subsequent intervention planning decisions may depend on the ability to recognise the essential identity of individual communities. Used to define the very basic information required, in order to formulate a minimum response to the stress situation. Once agreed upon, it cannot be altered, as this will corrupt all previous data. The primary agency or organisation that instigates a research project to determine a value of any given situation that it believes needs addressing. Information gathered that is not part of the core data but has value. Information gathered that is not part of the core data but has value. No country or organisation should intervene in any country other than to provide emergency relief under a United Nations flag. Any country or organisation can be involved with any project at the invitation of a host country or organisation. The lifestyle of any community is the essence by which a community exists and is often dependent on a typical livelihood or a cultural tenet. Any relief or development involvement must take into account these variables. Similar communities within a given area can be compared but cannot assumed to be representative of the whole area under consideration. As implied, this term provides a picture at a large or overall scale. This provides a picture where necessary, at a scale that is neither macro nor micro. In this context, the term marginal is used to describe core or variable data. It may refer to a community on the borderline of impoverishment, at risk of descending into an impoverished situation should an overall situation deteriorate. Can equally apply to the environment, agriculture, community members, etc. As implied, this term provides a picture at small scale. This provides a picture at a scale smaller than micro, when it is deemed necessary to do so.

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Poverty indicator:

Social indifference: Social preference Tour report: Variable:

Any set of validated statistics that shows a community or individual as below a set standard value of impoverishment. Caution is required on two levels. 1 – That many assumptions are made that do not consider important variables and 2 – that many indicators are set at macro level and have no relevance in a micro or local situation. This is where community members accept without question a given situation, not knowing or giving heed to any consequences. Can equally be termed as fatalism or habituation. This is where community members select an action to invoke a personal choice as being their prime choice. A report that accompanies the final presentation of the core data and acts as a source of incidental or informal information relative to the core data. A quantity that may take on any set of values. A variable can be any value that has a direct bearing with one or more values within a set of core data and / or has a direct consequence within the area of interest of a core data value.

a

The photographs depict a small business enterprise by a low-income family; to collect driftwood and sell this as fuelwood. The answer is ‘yes’ to both questions.

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Of Molehills and Mountains