avatar International Finance Corporation Finance, Insurance, And Real Estate

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    Esso Exploration & Production Chad I nc. Land Use Mitigation Action Plan Annual I ndividual Livelihood Restoration Report 2007 31 January 2008 \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 1 of 21


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    Executive Summary Since mid-2006 the Environmental Management Plan’s (EMP) Geographic I nformation System (GI S) and Socioeconomics groups have developed a number of survey tools designed to provide reliable data for future land acquisition and to review and filter out low quality data already in the Compensation Database. These tools are used to monitor and evaluate the impact of past land acquisition on inhabitants of the Oil Field Development (OFDA). The EMP Department achieved a step change in identifying At-Risk Households through the use of Village Land Survey Teams and Fast Track Mitigation Team Surveys. These teams along with the Land Use Mitigation Action Plan (LUMAP) Advisor (anthropologist/ sociologist/ economist) analyze this data to determine actual impacts on households and villages. These surveys are to be carried out in all seven (7) of the villages currently categorized as severely impacted. One village (Dokaidilti) has been completed and two more are well on their way (Ngalaba and Dildo). The same survey tools and questionnaires are also being applied to “Fast-Tracked” individuals who appear to be At-Risk in the EMP Compensation Database. The Fast Track Mitigation Survey Team is gathering data to determine their actual status and implement corrective actions as appropriate. The survey targets have been expanded to include people still surrendering land for Project needs, again in order to identify their potential risk. The Village Land Surveys (GI S mapping of fields and in depth socioeconomic questionnaires) provide much more accurate data than was available from the previously used Compensation Questionnaires (declarative by land user. For example, Dokaidilti: At Risk HH At Risk HHM Compensation Database 185 843 ( Declarative) Village Land Survey ( Real 13 110 Land) Fast Track Mitigation Survey Check on Cadastral 2 14 Data ( Real Land + Real I ncome) HH Household HHM Household Member This comparison clearly illustrates the value of these tools. I t is reasonable to expect similar data and results at the other severe and watch list villages. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 2 of 21


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    1. Purpose A critical task for the Land Use Mitigation Action Plan (LUMAP) is to identify households and individuals currently put “At Risk” by Chad Export Project land take, to assess how to rectify the situation, and then, to implement corrective measures that will mitigate their situation. The LUMAP team is also developing improved work processes for the EMP Department to use to identify potential at risk households, verify actual status and implement steps to restore livelihood or minimize impact in a timely manner using the EMP principles and procedures. Action Area 1 of the Plan addresses “I dentification & Assessment” by proposing to “Use various tools such as the project’s Geographic I nformation System (GI S) and field surveys to identify current and future project impacts at the village and individual land user level. The information from the identification and assessment process will then be used in other action areas to mitigate current conditions and to minimize future impacts. The I dentification and Assessment systems make it possible for the Project to apply the Environmental Management Plan in a more forward looking manner, assess cumulative land use impacts (total impacts over time) and predict areas of high potential land use impact.” Thus the GI S and survey tools developed to identify people already At-Risk must also be effective in identifying future situations when project impact is approaching the point at which people will be put at risk and facilitate timely implementation of EMP principles and procedures to minimize impact and/ or livelihood restoration. The purpose of the LUMAP’s Annual I ndividual Report is to provide information on the number of people currently at risk because of past project impacts and to convey the corrective actions that are in place or have been completed to resolve their situation. The efficacy of the LUMAP tools going forward will be demonstrated by this annual reporting on the numbers of individuals / households whose situations have been resolved/ improved or not further aggravated by the Project over the past year. 2. Database I ssues Associated w ith I dentifying People At Risk 2.1. Pre 2007 I ndividual Red Flag Process Early in 2007, a Red Flag Function was introduced into the EMP I nformation System (EMPI S). The Red Flag Function used declared data collected through the existing Compensation Process and included in the existing database. The EMPI S now automatically identifies (“Red Flagged”) the individuals e.g. resettlement factor less than 2/ 3 corde per household member (HHM) potentially eligible for resettlement. This Function was used to rapidly prioritize the livelihood restoration roster to target those with the least land. The following figure is a snapshot of the view used to identify Red Flag individuals. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 3 of 21


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    Figure 1 : View Used To I dentify Red Flag I ndividuals Compensated individual (see a row in the background windows), summary and detail information is provided in order to explain the resettlement factor (red cells column). By selecting an individual (selecting a row), the foreground window provides detailed information about each compensation file (each file is a row) related to him/ her in the database. The next table shows the same data displayed by the foreground windows. Table 1: Chronological Land Take of an I ndividual. Exact Land Cumulative Date Dependent Corde Take (Corde) Land Take 10/18/2001 6 21 0.301 0.301 4/11/2005 6 3 0.216 0.517 5/9/2005 5 8 0.816 1.333 9/26/2005 6 3 0.052 1.385 9/26/2005 6 3 0.026 1.411 10/3/2005 6 3 0.262 1.673 3/12/2007 10 1 0.521 2.194 \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 4 of 21


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    This table demonstrates how the declarative data reliability (Dependent and Corde) is less than adequate. As presented, answers are not consistent over time. I n this example, the individual started with 21 cordes for 6 dependents. Six years later, after a cumulative Land Take of 2.1 cordes, he declares that he has land use of only 1 corde. The above example is not isolated. Similar examples have been observed in OFDA over the years. The Village Land Survey at Dokaidilti validated the anecdotal observations leading EEPCI to adopt the Cadastral land Survey Methodology (See section 3). Nevertheless, the Red Flag Function has allowed us to classify individuals into two categories: Not Eligible and Potential Eligible. I ndividuals in the Potential Eligible category are targeted for an in- depth analysis using the Cadastre tools. The Red Flag Function produces the two categories as presented in the next table. Table 2 : Number Of I ndividuals Compensated I n 2007 By Village Individual Number of Red flagged Number of Village compensated not dependent Individual dependent eligible Abassana 2 8 2 22 Atan 0 0 1 12 Bayande 2 11 7 63 Béboro 1 9 0 0 Bedjondo 1 8 0 0 Bédobara 0 0 2 24 Bégada 25 147 28 273 Bégonlara 2 5 6 64 Béguirakol 14 60 6 45 Béla 28 135 26 261 Bémira 2 17 7 61 Bengonelara 4 10 19 143 Benguirakol 12 43 10 81 Béro 40 112 111 1051 Béti 0 0 1 15 Danmadja 1 1 14 113 Dildo 4 19 28 379 Doba 0 0 1 17 Dokaïdilti 17 71 39 392 Guirkou 1 7 0 0 Kagroye II 8 56 7 71 Komé 2 41 7 108 Koutou Nian 6 35 13 93 Madanan Nadpeur 1 10 0 0 Madjo 5 17 17 172 Madjo-Doba 2 6 3 24 Maïbo 0 0 1 9 Maïkéri 25 80 54 476 Maïkiro 1 3 5 33 Maïmbaye 5 25 9 75 Mainani 3 18 2 22 Maïnani 5 32 5 43 Mbanga 107 436 227 2232 \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 5 of 21


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    Miandoum 4 34 15 161 Missimadji 3 19 8 99 Morkété 4 20 4 19 Mouarom 16 58 37 305 Moundouli I 8 25 26 273 Naïkam 18 136 1 4 Ngalaba 36 132 76 674 Ngara 0 0 2 16 Poutouguem 24 98 73 700 Total 439 1945 907 8699 A total of 1346 individuals (the sum of columns 2 + 4) received compensation in 2007. The following column after the village indicates how many compensated individuals were not eligible for resettlement after compensation. The next column indicates the total number of declared dependents of those not eligible (Ex.: 2 individuals from Abassana were not eligible after compensation. These 2 individuals had a total of 8 dependents.). The next column indicates how many compensated individuals were potentially eligible after compensation (e.g. Red Flag indicating that their responses to current land holdings minus the amount being compensated left them with < 2/ 3 c/ HHM). Finally, the last column indicates the total number of declared dependents of those potentially eligible (i.e. the wider impact of the land take). The total number of potential eligible individuals is 907 representing 8699 dependents. The sum of both “Number of dependents” columns is about 10,600. By crosschecking this number with available demographic data, it seems that the computed value is too high. This is explained by the fact some respondents to compensation questions data mix up the concept of Land User and Head of Household (CdM), allowing a dependent to depend on two different individuals (ex: A husband is compensated and declares 8 dependents – 1 wife and 7 children. Later, his wife is compensated and declares 7 dependents – her 7 children. I n this case two (2) individuals were compensated, however, 15 dependents declared – the dependents were double counted). This is a Compensation System issue that needed to be corrected. I n order to correct this system issue, the household concept needed to be defined and built into the database in order to get a more realistic and accurate picture of any given household situation and then accurate data analysis for larger numbers of households. 2.2. Household concept Later in 2007 the Household concept was integrated to the EMPI S. With GI S mapping and household-wide surveys, the improved data allows us to gather individuals and their surveyed land into a Household, cutting down the redundancy problem described in section 1.1. For those individuals/ households, it is then possible to compute the resettlement factor based on measured data rather than data declared by individuals. By storing all Household survey results into the system, we now get a better picture of individuals and their dependents. The next figure illustrates the view used to analyze information on households as of now going forward. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 6 of 21


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    Figure 2: View Used To I dentify Red Flag Households The hierarchical view ( Treeview ) on the left part of the windows presents a list of village with icons that indicate their classification. User selects a village ( Node) and sees in the right part summary of information on households (e.g. series of rows, each row displaying a HH). All rows in red indicate that the resettlement factor is less than 2/ 3 corde per HHM (last column) and that whether the HH is “At-Risk” for lack of farmland needs further investigation. When viewing a village node in the tree view (next figure) all household data are displayed in details. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 7 of 21


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    Figure 3: View Used To I ndicate Details About A Particular Household After a household is selected, the treeview details the composition of the household (wife, children, and other dependents) while the right panel lists all compensation files and socioeconomic activities (surveys, resettlement) conducted with the given household. This view allows us to build the chronological sequence of all interventions (compensation, resettlement, etc) provided to a given household by EEPCI . The household concept is a major improvement in the way to collect and analyze data. Started in mid-2007, the Village Land Survey pulls together all information on a household. By surveying all the households plus the way land is being used and infrastructures of a given village we can get an accurate picture of the situation and find out who are the At Risk Households. These are the households who, even when pooling all the land resources of its various members, have too many dependents and too little land. These households’ living derived from agriculture will be very low and can be improved only by other ways of exploiting resources (e.g. fishing, sale of products from wild trees) or by the skills of its members (tailor, distiller of local brews) or the acquisition of additional land. I t also allows us to compare declared data obtained through the Compensation System (used for Red Flag computation) with the measured data of the Village Land Survey. The following section presents this comparison. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 8 of 21


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    3. Data Quality I mprovement Through the Village Land Survey Process The Village Land Survey performed in 2007 in Dokaidilti is interesting because declared data and reality were compared and a true picture of the agricultural impact on this village was developed. The following table presents all individuals compensated (Red Flag or not) in Dokaïdilti since the beginning of the project (computed on compensation data) in 1998. Table 3: Compensated Dokaidiltians since 2000 ( Compensation Database) Individuals compensated Number of Red flagged Number of Village not eligible dependents Individuals Dependents Dokaidilti 50 91 185 843 This next table presents all individual surveyed in the Village Land Survey of Dokaidilti (computed on Cadastral data). Table 4 : Dokaidilti Household Survey Nbr Household Nbr HhM Total 85 539 Not Eligible 73 439 Potential Eligible 10 100 Eligible 2 14 The Compensation Database indicated there are 235 compensated individuals (columns 2+ 4) with 934 declared dependents (columns 3+ 5). The Village Land Survey data accurately identified 85 households with a total of 539 dependents. The difference in the “number of dependents” is to 1: 2. This point highlights the fact that the Red Flag concept, when computed on compensation data, tends to overstate the potential number of At Risk Households and the impact of project land needs on a given village. Dokaïdilti’s Village Land Survey also allows us to compare the quality of declared versus measured data, such as “Number of dependents” and “Area cultivated by the Household”. The next table presents the declared & measured answers of the 71 CdM (head of household) that have been previously compensated in the village and also surveyed by the Socio-Cadastral team. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 9 of 21


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    Table 5 : Comparison Betw een Declared & Measured Data Declared Cordes Measured Cordes (Compensation) (Cadastre) Number of cord cultivated 6 12 Number of dependents 7 7 The difference between declared and measured cultivated area is a factor of 2. By using declared cultivated area to compute Red Flags led to an overestimation of the number of potential resettlement eligible people. The use of declared numbers of dependents and land holdings explains why, in Table 2, one hundred eighty five (185) individuals have been red flagged on the basis of their declarations while in fact only two (2) households (Table 3) are eligible on the basis of landholdings per capita in the household. The addition of Cadastral mapping and the grouping of inhabitants into households have considerably improved the quality of the data used to calculate resettlement eligibility. But several other elements also affect inhabitants’ economic viability. Since late 2007 a questionnaire has been administered as part of the land acquisition and Cadastral mapping process that addresses these factors as well as the household composition and agricultural status. These factors are economic and social: • Surveyed or compensated households may have other sources of income which supplement their agricultural production • The local concept of “dependent” is complex; one individual may provide certain kinds of economic support and declare the recipient a “dependent” although that dependent is also the beneficiary of other types of economic support from other household members. Some members of a household may, and frequently do, dispose of resources that they do not necessarily share with other members. Therefore the concept of “economic viability” must be examined at both the Household and I ndividual level. The Household provides a safety net for obtaining land and the support of its economic subgroups that draw on various resources not necessarily available to the entire household. An individual in the household may also have economic dependents that are outside the household. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 10 of 21


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    A Complex Household (This household is fictional but displays social characteristics extremely common in the area) Nadjingar, age 73, with three wives and 18 cordes of land. As the man who established the household concession (homestead) where most of his kin live, he is considered the CdM. Though he is crippled by arthritis and currently farms only 1 corde located within 0.5 km of the village, he is famous as a bone setter. • Wife # 1 was from the same village. She had 3 surviving children by Nadjingar but the land she inherited from her father and farmed to provide food for her children returned to her family on her death • Wife # 2, Nodjitel, is his distant maternal cousin from a village 24 km away. She has 3 surviving sons and 1 daughter by Nadjingar. She has moved back to her paternal village but never remarried so she is separated but not divorced. • Wife # 3, Denelelem, comes from the adjacent village but is no kin of Nadjigar. She has 2 surviving daughters by Nadjigar but she also has 2 boys, now teenagers, by her previous husband. She feeds all her children and Nadjingar from the 2 cordes he offered her plus 1 corde she borrowed from her brother in her nearby home village. She also uses the product of Nadjingar’s field which he gives to her as recognition of her services. What has happened to the surviving children? Wife # 1’s sons remain with their father. • Mbainaisem, the first born and first to marry has his house in the same concession as Nadjingar. • Wife # 1 lives in a separate concession in the same village that he built for her and her 3 children. She cultivates 3 cordes from her father and also sells local brew. She sends Mbainaisem a meal every day; she doesn’t send food to her father-in-law but makes sure Nadjingar always gets a bottle when she brews. Mbainaisem usually sends her half a sack of his home-grown grain each month and a washbasin full to his father Nadjingar. • Son # 2, Yotoloum, married and had 2 children, both of whom died. His wife left him because he took to drink. Today he is an alcoholic, living in the same concession with his father and dependent on the household for support. He eats with his brothers Mbainaisem and Rimasbe. • Son # 3 excelled at school and is now a civil servant in the capital. He sends his father 20 000 CFA each time he is paid, which may be anywhere from monthly to a 6 months gap. He has sent the two youngest of his 7 children to keep Nadjingar company and be fostered by their grandfather. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 11 of 21


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    Wife # 2 Nodjitel • Son # 1 was a trouble-maker. Eventually he moved to be with his mother in her home village. • Daughter, Neaobe, married a man from a nearby village but is now separated. She has come home with her 3 children to stay with her brother, Rimasbe. • Son # 2, Rimasbe, is a dedicated farmer. He has married two women from the same canton, both of whom help him farm his fields. They live in a concession next to Nadjingar’s. Nadjingar is supported i.e. fed mainly by these two daughter-in-laws who regularly send him meals, which he then shares with his grandchildren. Wife # 1 is barren, but # 2 is pregnant. • Son # 3 is about 18. He lives in the same concession but --is interested in marrying a village girl and has started farming peanuts in order to have enough money to make an impression on her. He eats with Rimasbe, his full brother. Wife # 3, Denelelem, • Laram, daughter # 1 has married and moved to town, where she makes beer and runs a cabaret. During the New Year’s festivities she always sends her mother 4 new dresses. • Daughter # 2 is living with her mother. She is old enough to undertake many of the household tasks. • Son # 1 by previous husband is unmarried and lives with his mother and half-sister. He is old enough to farm independently but since he has no kin in the village he has no access to inherited land or anyone who will readily pay his bridewealth. • Son # 1 is in his young teens. He still depends on his mother for support. From time to time he helps her farm but most of his time is spent “running with the boys”. He sleeps most of the time with the oldest of his companions who has his own house. The next table resumes the situation of this household while the next one presents the economic subgroups in the household. Table 6 : Summary of a complex household Nbr. of kin 36 Nbr living in Nadjingar’s concession 18 Nbr economically supported by ChM 6 Nbr Cordes available to Nadjingar 18 \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 12 of 21


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    Table 7 : Details of a complex household # Economic subgroups # cords available in the household 1 Nadjingar+ wife# 3 + 2 grandchildren 1 2 Wife# 3 + Nadjingar + 1 da + 2 sons 3 3 Son# 3/ wife# 1 contributes 20 000 CFA 0 4 Mbainaisem Son# 1/ wife# 1 + 2wives+ 7ch + bro + Nadjingar 3 5 Wife# 2/ Mbainaisem + 3ch 3 6 Son# 2 Rimasbe/ wife# 2 + 4si & ch + 2w+ 2bro (incl. Yotoloum) + Fa (Nadjingar) 6 7 Laram, Da/ Wife# 3 4 dresses 0 Nadjingar’s land in fallow 2 Pending I nheritance Claims for Son# 2/ Wife# 1 Yotoloum cordes Son# 3/ Wife# 2 Residual Family claims to cordes Son# 3/ wife# 1 Son# 1/ wife# 2 To comprehend this complexity the Land Acquisition team and Land Management Action Plan group are now using a detailed socioeconomic questionnaire as well as the Cadastral and Household survey teams. (See Appendix A for the questionnaire). \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 13 of 21


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    4. Red Flag Filter and Fast Tracking: The Village Land Survey and new socioeconomic questionnaire provide clear and accurate data about a household, its individual members, and its agricultural assets. The questionnaire also shows the economic subgroups and the assets and earnings available to each of them. Already compensated individuals deemed eligible for Resettlement Options have been evaluated based on the less reliable declared compensation data (discussed in section 1 above). Those below 2/ 3 c per HHM were investigated for other income sources which provided alternate support. Those with neither land nor other sources of adequate income were or will be offered the Resettlement Options. What has become of these various individuals affected by Project land needs? I n the case of those benefiting from Resettlement, it is dependent on how well they have fared through the resettlement option they chose. For those whose declarations did not put them under 2/ 3 corde, their situation is contingent upon the truthfulness of their declared dependents and land holdings. To test the current situation of individuals compensated in the past, the Land Mitigation Action Plan Team developed a Fast-Track Mitigation Survey Team to assess individuals and households livelihood status. Their findings are assessed by the LUMAP Advisor. The LUMAP Advisor then conducts further assessment and recovery planning through the LUMAP Counselor. As the first step, a data filter that draws on the correction factors learned in the Dokaidilti survey, shows compensated people that are more probably in difficulty. This filter is applied to all compensated individuals/ dependents whether “Red-Flagged” or not. This filter and fast track work as Figure 4 demonstrates: \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 14 of 21


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    Household Individual Individual Individual Fct Before first Land Take Resettlement - OK Fct During Land Take Eligible ? Yes Not Trained Fct After last Land Take Trained Training used ? No Yes Income Theoretical Other No From + Land Income other Used training Income Income Survey Survey Theoretical Actual Actual + Land Land Land Income Viable ? No Compute Theoretical Needed Actual Land Land Need What? Compute Help Land Theoretical Needed Land Compute Needed land from EMP (NBR dep. + 1) * 2/3 = Needed Land Needed Land – Actual Land = Land must get from EMP Figure 4: Fast-track livelihood process for individuals and households. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 15 of 21


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    5. Summary of 2007 The LUMAP has developed mapping and socioeconomic survey tools that give a complete picture of the household situation and resource availability in severely affected villages. The same tools are being used to provide far more reliable information about already affected individuals in moderately and less affected villages to find who needs to be “Fast Tracked” to recovery. Socioeconomic survey tools have been conjoined with monitoring results on the effectiveness of individual training in craft skills or improved agriculture techniques. When put all together into a filtering process it is possible to identify cases where households or individuals are truly at risk and in need. The improved identification process demonstrates how on the single criterion of land availability alone many fewer people are at risk than appear to be from declarative data given by affected people. The filtration process using additional economic income also demonstrates how many people are managing by farming and other activities to escape from deep poverty. For all these reasons Red Flag (computed on compensation declared data) should be used with caution. Table 1 presents an overestimated number of resettlement eligible people that is not totally grounded in reality. Despite this fact, Red flag plus Lessons Learned Corrective Factors is used by the Fast Track Team to target individuals that present the highest chance of eligibility for inclusion in the filtration process. Working on these two fronts, the situation in Dokaidilti is finished and Ngalaba and Dildo where Village Land Surveys are underway and 32 % complete at year end 2007. The Fast Track Team, which was trained, equipped and up and running at the beginning of December had surveyed 9% of possible at risk individuals in other villages. 6. 2008 Plan Five of the seven severely affected villages should be surveyed by mid-rainy season 2008. Survey productivity will drop greatly during the rains due to farmers not available and difficult access for the teams. However, the remaining two villages should be finished before the end of 2008. As each village is completed the LUMAP team will analyze the data, as has already been done for Dokaidilti. Compensation Database maps will be queried to show the previous cultivators of compensated land waiting to be reclaimed and returned. This information will be matched to the land needs of those land-poor households and any additional needs for Third Party Compensation calculated. Site Specific Plans for community recovery will be developed one by one according to the Site Specific Livelihood Mitigation Plan Framework that has recently been generated. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 16 of 21


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    People from other villages who are still at risk when filtered through survey and income information will also be consulted and counseled on livelihood recovery by means of increased income or additional land. One test to carry out in 2008 will be to survey a random number of project-affected individuals in moderate and less affected villages to test the accuracy of the filter. Even though Cadastral mapping of the villages will not be completed by rainy season 2008, the Dokaidilti analysis and Site Specific Plan demonstrated ways in which the greatest land needs of this community can be dealt with soon enough to provide people with more arable land for the 2008 rainy season. I n addition to priority reclamation of land that can be returned to At-Risk people, LUMAP will implement a new resettlement option which allows people to access land too far to be easily cultivated but not far enough to require moving to another village. An additional tactic for livelihood restoration is LUMAP evaluation of At-Risk individuals’ performance track records in Off-Farm or I mproved Agriculture training. For those whom the training has not yielded enough replacement income to compensate for land lost to the project, LUMAP will provide land through Third Party Compensation, or if necessary, through resettlement to make them viable. I n other cases, after discussion, additional training or other assistance may appear enough to render motivated individuals viable. The position of LUMAP Counselor has been created and begins in February 2008. The LUMAP Counselor will assist the At Risk person in developing a recovery plan. The recovery plan will utilize all of the options available through the Chad Resettlement and Compensation Plan as laid out in the Land Management Manual. An important tool in targeting training to those who can use it will be the initiation of literacy, numeracy and management instruction open not just to those At-Risk but to everyone in the village. I nterested people can profit to the degree they are willing to learn, but At-Risk individuals must demonstrate they can benefit from training before they can choose the Off Farm or I mproved Agriculture Training resettlement options. \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 17 of 21


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    7. Appendix 1. Identification du chef de ménage Prénom : ________________________ Nom du famille: ______________________ Autre noms : _______________________________ CIN ID de la base de données Année naissance Votre village de naissance : _______________ Village/champ saison pluvieuse_________________ Village saison sèche_________________ 2. Prénom du père : ………….……… Nom de famille du père : ……….………… Village de Résidence du père : même village même canton (nom du village ………………….) ailleurs Prénom de la mère : ……………… Nom de famille de la mère : ……….…… Village de Résidence de la mère : même village même canton (nom du village ………………….) ailleurs Est-ce que la personne enquêtée souffre d’une infirmité Parait-elle vulnérable? Maladie chronique Sourde Aveugle Vieillesse Handicap physique Handicap mental Alcoolisme évident Autre……………. 3. Habitez- vous ce village depuis toujours? Oui Non Si non : Êtes-vous venu………… Depuis mon mariage Avant début du Projet Après début du Projet Venu à cause de…… Un parent Chercher des terres Chercher travail Esso Affectation Service Commerce Préfecture d’origine ……………………….. Groupe ethnique ………………………….. 4. Qui est-ce que vous donne à manger? Moi-même Mon père Ma mère Mon mari Grand parent Autre……………. Observations :……………………………………………………………………………………………………………………………… 5. Combien êtes-vous dans la maison Enfant et adulte de chaque catégorie qui dorment et mangent tous les jours chez vous, depuis au moins 6 mois Homme 16ans+ : Femme 16ans+ : Enfants 6-15 ans : Enfants 0-5 ans : Non Nucléaire : NE PAS INCLURE dans le total les enfants venus au village pour les vacances INCLURE les enfants partis pour les vacances 6. Parmi les hommes de plus de 16 ans, combien ont ou sont : Un travail Un travail Un commerce Chercheur chez Esso : __________ non-Esso : __________ régulier : _______________ d’emploi :_____________ Ne cherche pas : ________ 7. Avez-vous dans votre maison des enfants qui fréquentent? Concerne tous les enfants habitant à la maison + les enfants directs qui fréquentent ailleurs Sans enfants Ne vont pas à Collège Lycée Université Enseignement en âge l’école (6-15 École (jusqu’en 3e) (2nde – ou grande technique (tout \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 18 of 21


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    scolaire ans) primaire bac) école genre) 8. Parlez-vous Français? Oui Non Lisez-vous Français ? Oui Non Savez-vous écrire ? Oui Non 9. Quel est le niveau de scolarité que vous avez atteint? Aucune scolarité École primaire Collège Lycée Université ou Enseignement (jusqu’en 3e) (2nde – bac) grande école technique (tout genre) 10. Avez-vous déjà reçu une compensation? Non Oui Si oui combien de fois? :_________ Numéro IN : _____________ Avez- vous déjà reçu une formation Non Oui Si oui, formation en quoi ?______________________________ 11. Quels sont vos activités habituelles? Marquez X pour le répondant, A pour un autre dans la maison Vous- Agriculture Élevage Agent de Dibiterie/ Commerce Petit Pêche Chasse même l’état Boissons commerce Artisan Manœuvre Petits Maraîcher Journalier Moso Inactif Autre boulots Esso 12. Votre rendement agricole de la dernière saison. Combien de sacs de…… Culture Mil pennicillaire Sorgho Arachide Sésame Riz Autre……………. Nombre de sacs 13. Combien gagnez-vous par semaine avec la chasse/pêche/boulots/maraîchage ? Saison sèche ________________ Pluvieuse________________ 14. Avez-vous actuellement un travail rémunéré? Oui Non Si oui : Artisanat Salaire Si métier, lequel _____________ Combien gagnez-vous avec ce métier par semaine? ________________ Comment avez-vous acquis ce métier Esso Parent Apprentissage Si Salaire : Un salaire Un salaire Salaire Gardiennage De l’argent régulière d’un Sans salaire, ni Non-Esso journalier permanent Une pension/retraite parent de la ville pension, ni argent de Esso Esso qq Salaire annuelle de plus + OU de moins – de : 100 000 FCFA 50 000 FCFA 15. Quel sont les sources de revenus du ménage? Agriculture traditionnelle Cultures de rente Maraîchage Artisanat Petits boulot Pêche Chasse Beignets/bouillie Timbrier Moso \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 19 of 21


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    Boissons locales Charbon de bois Élevage Travail salarié non Esso Commerce Pension/Retraite Loyers Argent reçu de parents Travail salarié Esso vente matériels obtenus grâce à la Autre …… Sans revenus compensation/salaires 16. Avez-vous vendu (ou gagné) plus ou moins que 50 000 (entre 50 et 100 000) ou plus de 100 000 FCFA depuis la dernière récolte? Indiquez les activités génératrices avec - 5 ou + 5 ou -10 ou + 10 Agriculture traditionnelle Cultures de rente Maraîchage Artisanat Petits boulot Pêche Chasse Beignets/bouillie Timbrier Moso Boissons locales Charbon de bois Élevage Travail salarié non Esso Commerce Pension/Retraite Loyers Argent reçu de parents Travail salarié Esso vente matériels obtenus grâce à la Autre …… Sans revenus compensation/salaires 17. Avez-vous reçu de la compensation d’Esso? Oui Non Si oui, combien de fois………… 18. Est-ce que d’autres de votre ménage ont reçu de la compensation d’Esso? Oui Non 19. Dot Combien de dots avez-vous payé avec argent de la compensation? ………….. Avec l’argent du salaire? La dot pour (parenté)…………… 20. Qualité de la maison principale construite par Esso par argent compensation par salaire par moi-même Toiture Tôles Paille Terre Toit provisoire (bâches, plastique) Terre simple Brique terre Briques cuites Semi-dur Dur Murs Seko Tôles Planches (partiellement) (terre+ciment) (parpaings + ciment) Sol Tout en terre Partiellement cimenté Complètement cimenté Carrelage 21. Que possédez- Salon moderne rembourré, vous comme Sans meubles Salon en rotin Salon en bois Bois+coussin couvert de tissu meubles? 22. Comme Carton lit? Lit Local Lit Manufact. Matelas paille Matelas coton Matelas coton Matelas éponge Natte /Rien 23. Latrine Sans latrines Latrine plein air Latrine entourée Latrine couverte WC intérieur Vérifiez partagée partagée partagée partagée avec chasse visuellement d’eau 24. Utilisez-vous des moustiquaires? Non Oui Combien pour le ménage \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 20 of 21


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    25. Dites-moi quelques choses concernant vos bétails : Bœufs Combien achétés avec argent de la compensation?................ Avec l’argent du salaire?............. Argent d’Agriculture?..................... Avec les naissances de votre bétail, combien de bœufs avez-vous maintenant? ………………….. 26. Que possédez-vous comme équipement? Indiquer si obtenu grâce à la Compensation (C) ou aux salaires (S) d’Esso ou par propre argent d’Agriculture (A) Indiquer le nombre si supérieur à 1 Charrue A - C - S Pousse-pousse A - C - S Équipement de maraîchage A - C - S Motopompe A - C - S Fusil A - C - S Équipement de forge A - C - S Téléphone mobile A - C - S Moulin à mil A - C - S Grandes Matériels de cuisine A - C - S Radio qui fonctionne A - C - S Machine à coudre A - C - S Décortiqueuse A - C - S Moto ou mobylette A - C - S Voiture A - C - S Machine pate d’arachides A - C - S Vélo A - C - S Groupe Électrogène A - C - S Fonds de commerce A - C - S Charrette à bœufs A - C - S Boutique A - C - S Aucun équipement A - C - S Corps butteur A - C - S Gargote/dibiterie A - C - S Rien Si la réponse est « Rien » mais le répondant/quelqu’un du ménage a reçu de la compensation ou salaire, demandez comment c’est disposé ……………………………………………………………………………………………………………………………………………………………………… ……………………………………………………………………………………………………………………………………………………………………… …………………………………………. ……………………………………………………………………………………………………………………………………………………………………… ……………………. ……………………………………………………………………………………………………………………………………………………………………… ……………………. Signature EEPCI Signature de l’Ayant Droit \ \ CHDKMEFN001\ epbrown$\ Data\ EEPCI \ Lenders\ I FC\ 2007 updates\ EEPCI - LUMAP - Annual I ndividual Livelihood Report - 2007 - Final.doc Page 21 of 21


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