Urban Poverty and Data Gathering Techniques (Q2)-Education Slums and education: findings form GTZ sponsored study in Bangladesh: Luigi Peter Ragno (with Nadia Goodman) Social Protection and Livelihoods expert GTZ Objective: Enhancing the participants’ understanding on the existence of complex relations among education (measured by school attendance) and other dimensions’ of people’s livelihoods. Promote the use of both quantitative and ethnographic approaches to identify such relations The session will • Introduce the GTZ sponsored Livelihoods study in 6 slums of a secondary city in Bangladesh focusing on the data gathering and analytical tools adopted. • Present key findings and dependencies identified: education and food security, education and housing environments and education and land • Conclude that educational policies and projects must take into account other dimensions of people’s livelihoods and that illiteracy and low education levels are the negative results of coping strategies to address sudden and slow onset shocks which hinder the achievement of basic and immediate needs (primarily food); this prevents households from investing in longer term priorities, such as sending their children to school. Illiteracy is therefore the result of a survival strategy rather than simply the consequence of a lack of infrastructure and high school fees, and, as such, must be addressed in a holistic way.
This session is based on GTZ sponsored Livelihoods Study on Urban Poverty prepared in collaboration with the Municipality of Narayanganj
This presentation is based on the recent work of GTZ in Narayanganj Municipality in Bangladesh which attempts to provide policy makers at local and national level information and data on urban poverty in secondary cities. This socioeconomic baseline study was the result of a collaboration 1 between Narayanganj Municipality, the World Bank and the Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH, to support the Municipality in creating an instrument to identify all the poor urban settlements and pockets of urban poor in the Pourashava 2, as well as to provide valuable and reliable information, data and technical assistance to support the design of a forthcoming urban National Social Protection Project. Objective of the Study
1 2
Between April and December 2008 Pourashava is the Bengali word for Municipality and refers to the 309 Secondary Cities of Bangladesh
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The overall goal of the joint intervention is “providing the policy arena with concrete data and updated information on poor urban settlements in secondary cities as well as promoting an in depth understanding of urban poverty in Narayanganj.” More specifically, the study’s objectives are: •
to provide a comprehensive and detailed multidimensional baseline of information and trends that can be compared with a post-implementation baseline to identify changes in poverty dynamics after the implementation of any project;
•
to promote people-centered policy design in Bangladesh - the participatory analysis, as a starting point of the discussion with the community, gives a voice to people that policy makers must listen to and use as framework for any intervention;
The study’s concept bases on a number of assumptions best summarized by Jones/Rakodi: ‘Urban poverty is a series of interlinked difficulties ……a reinforcing cycle of problems that the poor face………..in term of security, safety, well being and access rather than in terms of poverty. Access is a key factor in an urban context……….Without understanding these issues and the multidimensionality of livelihoods strategies, action in one sector may not have the intended impact or may affect people adversely ….. increasing their insecurity”’ 3 Thus, the study is predicated on the argument that poverty is both the cause and effect of many inter-related factors that reinforce each other and cyclically reproduce themselves. These ideas have been logically and systematically incorporated into the ‘Sustainable Livelihoods Framework’ developed by DFID which can be used as an analytical tool in understanding people’s livelihoods and poverty. It is also a tool to shape policies and interventions to address the vulnerability context through enhancing people’s livelihoods. The Framework has therefore been adopted as the conceptual framework for this study.
Methodology Quantitative techniques (such as a socioeconomic survey) and qualitative techniques (such as focus groups discussions and semi-structured stakeholders interviews) were combined with a review of secondary sources to produce the study. This approach enabled emphasis to be placed on the dependency and inter-linkages among different people’s assets and the need for an indepth understanding of households’ livelihoods strategies and perceptions 3
Sue Jones p. 277 in Rakodi, C., T. Lloyd-Jones, et al. (2002). Urban livelihoods : a people-centered approach to reducing poverty. London, Earthscan
2
The combination of quantitative and qualitative approaches in both the information gathering and analysis stages allowed for a ‘Participatory Analysis’ of the data, which merged technical/expert and the community’s understandings of the information gathered and enabled strategies and approaches to be adopted that were rooted in people’s perceptions (Triangulation Methods).
Triangulation method The study was built around the inter-linkages among key aspects of people’s complex livelihoods. Therefore, in order to identify strategies that might contribute to tackling these inter-related challenges, trends and dependencies among variables included in the socioeconomic survey were analysed. As discussed earlier, an analytical framework was developed and several hypothesis were tested. To understand such complex settings, an analytical matrix was prepared and several hypothesis tests (using models such as Tukey HSD and Chi-Square Test) were run with the gathered data to identify key issues that have been presented in each section of the study. Each stage and tool used in the study is explained below to show how it contributes to the overall aim and answers the main question proposed by this work.
Preliminary Urban Poverty Assessment. The first step to get an overview of the situation has been identifying all poor settlements within Narayanganj Municipality. Those settlements can be divided into 161 pocket areas (less than 50 Households) and 39 poor communities.
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To gain initial data on those poor settlements, focus group discussions were held in each neighborhood. The aim was to enhance the understanding about the five dimensions of poverty: Income, Health, Education and Services, Security and Empowerment. This approach contributed to gain information on the number of people and children, employment, schools, health centers, condition of housing, land ownership, water, drainage, sewage, latrines, gas, electricity, roads, open spaces, NGO involvement, community groups and voter registration.
Selection of the area. In order to have a more comprehensive understanding of the living situation within urban poor communities in Narayanganj the objective of the second step was to conduct a in depth socioeconomic baseline survey and to produce a physical map of the areas. This step, because of the human and financial resources as well as the time required, focused on 6 sums of the Pourashava. To select the 6 areas (out of the 39 identified), the GTZ initiated a sharing and consultation process with representatives of NGOs and the World Bank, ward councilors, area chairman, Narayanganj Pourashava officials and journalist that
were invited to discuss and
propose the areas in a workshop in Narayanganj. The selection process started with analyzing the location of the majority of Urban poor settlements and its population using as administrative cluster, the Ward. Four Wards were selected as it was identified that more than half of the urban poor lived there. The potential start of the pilot of the NSPP also had an impact on the final ward selection as a confined (the 4 wards selected are adjacent to each other) area for pilot would provide better control, monitoring and lessons learnt. Within each ward, to be able to get heterogeneous areas regarding to infrastructure, landownership, number of households, living conditions and locations within the city, 6 urban poor settlements (no pockets were included in the sample) were selected, for a total of around 2300 households living in the areas 1. Railway No. 1 2. Rally Bagan 3. Rishi Para 4. Jimkhana. 5. Sweeper Colony 6. Deara.
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Socio-Economic Survey: Design The questionnaire used for the baseline survey was developed on the basis of experiences made during the focus group discussions, suggestions from the communities, and with consideration of other poverty assessment survey questioners. The survey was designed as tool to collect in depth information and to provide a comprehensive overview of the livelihoods of the population living within the selected urban poor settlements. The survey questionnaire solicited data about: •
Demographic background: Religion, ethnicity, size of household, education
•
Housing security and land ownership
•
Income, expenditure and assets
•
Heath, Nutrition and Services: Sanitation, water, electricity
•
Empowerment: Engagement in local organizations, voter registration
•
Gender and equity
The questionnaire was developed in English and shared with experts on urban poverty and World Bank and UNDP; the final version was prepared and translated into Bengali. During the survey process five questions regarding migration were added to address the floating population which was larger than expected. Implementation: Prior to conducting the fieldwork 12 enumerators and four supervisors were selected. They were through a ten days course that included a three days theoretical training on poverty, livelihood framework and how to approach the households and seven days on practical field testing application during which
250 questioners were pre-tested in Kumundini Kampur, Kumundini
Metro and Isdair Railgate areas. This practical training in three pockets •
Provided the enumerators with practical experience in interview techniques
•
Allowed the team to adjust and finalize the questionnaire prior to commencing the actual survey; and
•
Reduced the potential for enumerator errors during the survey process
The baseline survey was applied to 2213 households out of the 2233 people who live within the six selected poor communities. This amounts to about 99.4 % of all inhabitants. The missing 0.6
5
% were absent, moved to another area during the survey process or could not be included in the household definition (to eat out of one cooking pot) for the reason that they do eat outside of the six areas. A detailed GIS mapping of the 6 areas was also implemented to support the implementation of the survey as well as the better understanding of physical space of the areas. The survey in each area followed this process: 1. With the aid of the respective community and the local Community Development Committees (CDC) a census was followed by a marking process in which every household received a unique number 2. After those initial preparatory steps, the enumerators visited every household to apply the questionnaire at different time of the day to be able to interview every individual family. 3. Each individual enumerator completed approximately 5 to 6 questionnaires per day. The total survey process took about 58 days, between the 20th of August and the 25th of October with 9 holidays. 4. To guarantee high-quality data, for every three enumerators one supervisor was assigned to monitor the survey process. In turns the supervisor crosschecked with one of his enumerators and reviewed the interview material of all three enumerators every evening. After a preliminary review of data by the supervisor the GTZ project officer rechecked the daily interview material and certified the process.
Descriptive and Participatory Analysis The data collected during the survey were entered through a specifically designed visual basic platform and stored in Access. Then a SPSS database was designed and all information transferred and cleared ready to be analyzed. The presentation of the descriptive data always starts with average results (either frequencies or percentages) of different variables and then, if it is identified that considerable changes would occur if disaggregated (cross-related) by area or other variable, the finding is reported and explained.
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Comparison and cross-relation of data among areas, income groups, education levels, religion has been done comparing percentages of cases rather than frequencies: this approach has allowed to identify tendencies and dependencies among key variables. National and Pourashava statistics used for comparisons have been sourced from the Bangladesh Bureau of Statistics. The standard statistical analysis through the SPSS was complemented by an ethnographic approach known as Participatory Analysis which has allowed the team, a pat from analyzing information gathered through the survey, further investigate issues that the questionnaire can miss. Participatory Analysis The process started from the conceptualization of the participatory analysis which leaded the team to establish of a set of findings (mostly from the survey) for discussion and analysis, with the active participation of the community people. The participatory analysis was conducted through a series of community workshop in selected urban poor settlements in Narayanganj. The urban poor settlements were selected by the EMGPR team and a conceptual framework together with a detail work plan for the analysis including the selection of tools, were designed with key stakeholders. Six community workshops have been carried out in the study area. For each workshop 20 participants were chosen and split in four groups. The finding discussed in a particular area was selected based on the initial urban poor mapping report
as
development
well
as
discussion
with
Town
planner
officer,
Area of
Narayanganj Pourashava; Project manager and Field supervisors of GTZ.
Group works in a community workshop
The 20 participants for each workshop were selected based on some agreed criteria which were decided considering the issue as well as the demographic composition of the area.
After
completing the five workshops all the findings were compiled and were presented in a sixth workshop where four participants from each previous five workshops were selected based on their willingness to join and six participants from the remaining area were invited. The purpose was to present all the findings of the previous workshops and to all participants from six areas and make necessary adjustment, correction and also take views from different participants.
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The workshops were designed and implemented in a systematic manner. All the research questions were asked through the tools, group works and participants comments were collected in flip chart. At the end of the sixth workshop a draft participatory analysis report was prepared and shared with EMGPR team; the final report was adjusted according to the feedback and comments form the EMGPR team. The main tools used in the Participatory Analysis have been Transect walk It provides a very quick view of the area visited. Before each workshop in each areas the team visited the area to get a quick picture of the areas. Pie chart It has been used to present and validate the survey findings during the workshop. In each workshop the relevant topics results were situated within the pie chart and was presented and discussed with the participants. Scour causal diagram This tool was used for identification of main root problems for every issue as well to identify the main causes of the problems. For each problem participants were asked to give marks out of 100. Then from the top two or three problems from each group the team proceeds to identify their coping strategy as well as what external support they needed.
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Presenting the survey findings through pie
Identification
of
problems
chart
through scour causal diagram
and
cause
Mood meter This tool was used to identify present status of some service facilities in their area; means what is their satisfaction level or perception on that. Time line Some times it becomes necessary to find out the time of a particular problem or their causes. This tool helps us to document history of issues and problems. Matrix Matrixes are used to identify community coping mechanisms of the identified root problems as well as to identify the type of external support they needed.
Mood meter tool to identify perception on
Matrix to compile problems, coping strategy
service facilities
and external support needed
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Group formation process The type of participants for each workshop was drawn from the quantitative survey findings and in discussion with EMGPR team and the Pourashava staff. The participants were grouped based on the criterion and the participatory analysis was facilitated through sub-group wise to capture an analysis from a group of homogeneous people. Workshop
Poor
number 1
Urban
Issues
Participated groups
settlement Rali Bagan south
Discussed Gender, Equity
Minority, Working women, Ultra poor,
2
Sweeper colony
and Practices Health
&
Working student Old age, Woman headed household,
3
Rail gate 1
Education Income
&
Ultra poor, School going children Minority, Old age, Woman headed
4
Rishi para
Liabilities Empowerment
household, Working people Minority, Old age, Woman headed
5
Zimkhana
Security
household, Working people Minority, Old age, Woman headed
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All five plus Deara
All & open
household, Working people Mixed group. One participant from each group of each area and same
criteria participant from Deara Table 1: Areas and issue discussed during the participatory Analysis
Geographical Mapping of urban poor settlements The GIS mapping of the areas selected has supported the implementation of the survey as well as the analysis of the data gathered. The process to create those maps was made of 5 different steps: 1. The first step was to identify preexistent maps of those areas as an initial reference. General and outdated map from Narayanganj Pourashava showing the main road supported the delimitation of the survey areas. After defining their survey areas, the students (and local assistants) utilized two different techniques: the Open Traverse Method and Global Positioning System (GPS) to take roads measurement. With the Open Traverse Method, a first fixed point is chosen as reference, and then sequential measurements of lines and angles following roads and pathways are taken to create a
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route. During this process, key points are identified in GPS. The result of this process is the base map of the areas. 2. In the second step, the axes of measured roads are drawn in the autoCad program, while the GPS points are transferred to arcGIS program. As soon as both drawings are complete they are superimposed in order to minimize mistakes, which are natural consequences of both methods. 3. In the third step, the final version of road map is once again printed and sent to the field to start a second survey process to collect further data on the type of use of these structures, the identification of houses according to socioeconomic survey numbers and identification/location of infrastructure equipments. To support this collection of data, the student had three kinds of forms, where they should fill in, list and identify each house, measurements and type of use. 4. The forth step was the conversion of the final road maps from ArcGIS program to AutoCAD program. Once done, the field measurements and location of structures and infrastructure equipment was added to the same file. 5. In the step 5, these structures and road maps were again transferred to arcGIS to develop referencing and identification process. The identification is done per household and structure following the identification number which is marked on house walls. The other structures are identified per type of use. At the end of this step, a final map were ready to be printed and used as support tool for the socioeconomic survey. The purpose of the GIS mapping a part from supporting the implementation of the survey will be further analyzing the spatial dimension of urban poverty through a dynamic software that will link the maps with the socioeconomic survey. The software will allow the creation of thematic maps (such as education, income, illness) and provide an addition tool to understand urban poverty.
The process itself, a part from guaranteeing high quality data as well as promoting the people centered research, was used as tool to report back and share with the communities involved the main findings of the study and piloting approaches useful to improve and promote good local Governance practices. --------------------------------------------------------------------------------------------------------------------------------Findings on education:
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Education. The surveyed areas are characterized by a very low education level with an average of 60% of the heads of households having not attended school at all. Again, there is considerable variation between areas with only 33% in Deara having not completed any education, while in Rishi Para and New Jimkhana the percentage is higher then the average (at 73.7% and 65.1% respectively, refer to Table 2). Completed
Name of the Area 1 No.
Class
No Class Class I-III Class IV-V Class VI-IX SSC/HSC Graduate /Masters
Total
Rail
Rally
Rishi
Jimkhan
Sweeper
Gate 47 40.9% 8 7.0% 22 19.1% 25 21.7% 6 5.2%
Bagan 259 57.2% 44 9.7% 67 14.8% 61 13.5% 9 2.0%
Para 350 73.7% 44 9.3% 40 8.4% 18 3.8% 3 .6%
a 500 65.1% 54 7.0% 90 11.7% 81 10.5% 25 3.3%
Colony 75 50.7% 17 11.5% 34 23.0% 11 7.4% 2 1.4%
Deara 85 33.5% 25 9.8% 36 14.2% 57 22.4% 37 14.6%
1316 59.5% 192 8.7% 289 13.1% 253 11.4% 82 3.7%
1
1
1
3
0
8
14
0.9%
0.2%
0.2%
0.4%
0.0%
3.1%
0.6%
6
12
19
15
9
6
67
Did not attend School
but
can read/write 5.2% 2.6% 115 453 100.0% 100.0% Table 2: Education profile in each
Total
4.0% 2.0% 6.1% 2.4% 3.0% 475 768 148 254 2213 100.0% 100.0% 100.0% 100.0% 100.0% poor urban settlement. Considerable differences in the
illiteracy rate can be identified across different areas: from almost 74% in Rishi Para to 33% in Deara When the education level of the head of the households is correlated to other variables, the existence of factors that shapes the education variable itself and the reproduction of its geographical differences is clear.
As expected, the education level of the household also has an impact on their income level. Income is directly linked to education and increases proportionally with the class of education completed. Even if the majority of the population is illiterate, the percentage of cases with ‘no education’ still declines when the income group is higher.
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90
100
80
90
70
80
60
No Class
50
Primary
40
Class VI-IX
30
SSC+
20
70 60
No Class
50
Primary
40
Class VI-IX
30
SSC+
20
10
10
0 Below Tk. 1000
Tk. 10003000
Tk. 30005000
Tk. 50007000
Above Tk. 7000
Trends between education level and income groups.
0 Below Tk. Tk. 1000- Tk. 3000- Tk. 5000- Above Tk. 1000 3000 5000 7000 7000
Percentage
of
cases
within
each
income
group
disaggregated by education level. Both Figures show how the education level of the households positively affects the income of a family: the higher their educational level, the higher their income group.
While in this case the correlation between income and education level is reciprocal as they influence each other (low educated households have less opportunities in accessing better paid jobs and low income induces households not to invest in the human capital dimension), the education level of the school- age children is directly dependent upon he education level of the head of the household. Percentage of children going to school increases proportionally with the education level of the head of the household.
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100
80
% of Cases
% of Cases
80 60 40 20 0
60 40 20 0
No Class
Class I-III
Class IV-V
Class VI-IX
SSC & above
Below Tk. 1000
Tk. 10003000
Education Level
Tk. 30005000
Tk. 50007000
Above Tk. 7000
Income Group
Percentage of school going children and education
Percentage of school going children and income
level of the household head.
Clearly, when the
group of household head. The income of the
education level of the household head increases,
household positively influences the percentage of
the percentage of school going children increases
school going children.
proportionally. Also, when comparing Table 2 and Table 3 which present respectively the education level of the head of the household and of the school age children disaggregated by area, similar percentages of cases are found. This finding implies that education level of school age children is mostly defined by both the head of the household’s education level as well by the place of residence. Name of the Area
% of Children (4-15 old)
years NOT
attending school 1 No. Rail Gate 33% Rally Bagan 37.5% Rishi Para 52.5% Jimkhana 62.5% Sweaper Colony 40% Deara 33.5% Table 3: Percentage of children not attending school, disaggregated by area The data on education also illustrates two important findings: the gender ratio among children attending school is, on average 4, more favorable to female children (55.7% versus 44%) and that the majority of children attending school are also involved in some kind of work, either inside or outside the household.
4
Up to a certain education level, usually primary, girls enrollment is often higher than boys. However, at some stage girls begin to drop out more than boys (http://www.irinnews.org/Report.aspx?ReportId=82444 , accessed on 13/02/09)
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The data on the working children demonstrates that, contrary to expectations and to the trends identified in Table 2 and 3, the incidence of working children is higher in better off areas such as Deara (71%) and lower in New Jimkhana (53%) and Rishi Para (58%).
90 80 70 60 50 40 30 20 10 0 No Class Class I-III Class IV-V Class VIIX
SSC & above
Percentage of working children within the education level of the household head. Interestingly, the number of children that work inside or outside the household, increases when the education level of the head of the household increases
Furthermore, when the percentage of working children is cross-related to the education level of heads of household, both variables increases:
in other words, households with a higher
education level are more likely to have their children working (as well as studying) than household with lower education levels. In summary, the data shows how the literacy and education levels of household members are strictly dependent upon the income level of the household itself and that it increases proportionally to the income. Furthermore, the education level of the head of the household influences and shapes the literacy rate of the school age children in the same household, highlighting the cyclical nature of the reproduction of inequality in education. In addition to this, data on working children illustrates that many children do attend school and at the same time work, inside or outside the household, and that the incidence of working children is higher in better off areas.
Empowerment This section of the study profiles the behavior of households on issues related to involvement and participation in community organizations, interaction with government officials, as well as how these issues are influenced by education and income levels.
The case of a community
organization in Rishi Para has been looked at in detail and important links have been identified
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between the membership of a household in that organization and their belonging to a specific income group. The education level of households also determines their participation and involvement in CDCs. The findings show that 67% of households with no education are members of the CDC, while for more highly educated households, an average of 86,3% participate. Households with a higher education level are more likely to appreciate the importance of being part of community organizations, while households with lower education are not able to maintain a high percentage of participation for a variety of endogenous factors (such as lack of time or financial resources to pay the monthly fee) and exogenous ones (such as financial barriers, exclusion by other members).. However, it is also clear that membership of an organization does not guarantee participation in meetings, as the majority of people have only attended meetings between 1 and 3 times (36% of the cases) or between 4 and 6 times (32%), and only 11.3% of the respondents had participated in more than 10 meetings. Also, attending a meeting does not necessarily mean participating in the decision making process. More than 52% of respondents had never contributed to any decision taken in a meeting of the association or group of which they were part. However, the findings also show that in religious meetings more people participate and contribute to the decision making process (30% compared to 23%). Education and income also play an important role in the likelihood of contributing to decisions. In Rishi Para, residents with higher incomes and higher education levels were more likely to have been involved in decision making processes compared to those respondents belonging to lower income and educational groups. Education and illiteracy as coping strategies. Without entering into the debate on the role of education and development5, in this study, a relationship of dependency between education and several other variables such as income, participation in community organizations and health issues was identified. It appears that education influences and determines the income and well being of families and vice versa. Furthermore, the education level of the head of the household also determines the level of education of the children, perpetuating the existing inequalities and status quo within the community.
5
Education as a tool to control, to exercise power and to maintain the status quo rather than education as freedom.
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Illiteracy and low education levels are the negative results of coping strategies to address sudden and slow onset shocks which hinder the achievement of basic and immediate needs (primarily food) and prevent households from investing in longer term priorities, such as sending their children to school. Illiteracy is therefore the result of a survival strategy rather than simply the consequence of a lack of infrastructure and high school fees, and, as such, must be addressed in a holistic way. As a result, literacy cannot be increased simply by building more schools. Other factors such as the household’s immediate needs - for example access to sufficient food; improved cooking and studying environment 6 and the promotion of adult education are also important issues.
Key Readings
Hossain, S. (2008). "Rapid Urban Growth and Poverty in Dhaka City." Bangladesh e-Journal of Sociology. 5(1). Kindon, S. L., R. Pain, et al. (2007). Participatory action research approaches and methods : connecting people, participation, and place. London ; New York, Routledge. Maine, R. A., B. Cam, et al. (1996). Participatory analysis, monitoring and evaluation for fishing communities : a manual. Rome, Food and Agriculture Organization of the United Nations. Mitlin, D., B. Sen, et al. (2005). "Chronic poverty." Environment and urbanization 17(2): 1-216. Pryer, J. A. (2004). "Poverty and vulnerability in Dhaka slums: the urban livelihoods study." Development policy review 22(1): 122-123. Rakodi, C., T. Lloyd-Jones, et al. (2002). Urban livelihoods : a people-centred approach to reducing poverty. London, Earthscan. Salway, S., S. Rahman, et al. (2003). "A profile of women's work participation among the urban poor of Dhaka." World development 31(5): 881-901. Sen, B. (2005). "Pulling rickshaws in the city of Dhaka: a way out of poverty?" Environment and urbanization 17(2): 11-25. Wodon, Q. T. (2000). "Microdeterminants of consumption, poverty, growth, and inequality in Bangladesh." Applied economics 32(10): 1337-1352.
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During the participatory analysis, the issue of smoke inside the shelters was directly linked with the low performance of the children.
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