Mohammad Zahirul Islam1 and Mohammad Amirul Islam2
1Institute of Regional Science/Planning, Karlsruhe University,
2Division of Social Statistics, University of Southampton
Since Bangladesh approved of the Millennium Development Goal (MDG) of universal primary education by 2015, a little has been done to reach the target. In Bangladesh primary schools are established by private initiatives. As a result an integrated strategic plan is absent. This research aims to suggest future primary schools, as well as their locations for Savar upazilla, a sub-district of Dhaka district in the light of the MDG by using GIS techniques (ArcView).
Census data along with other published and unpublished secondary data and maps from different sources have been used in this study. Primary school going children have been projected for Savar upazilla for 2015 using exponential model of population projection. Considering the projected primary school going children and following the guidelines of installing new primary schools suggested by the government, number of new primary schools required for Savar upazilla has been estimated. The suggestions of future primary schools and their coverage have been made in a systematic manner keeping the feasibility in mind. A build up area has been made to suggest the location of new schools excluding the existing roads with possible future expansion and the water bodies with possible extension during annual flood. The locations of these new schools have been identified and finally mapping of these new schools has been made. The results indicate that government should be involved directly in establishing new primary schools along side the private initiatives to achieve the MDG.
E-mail: islam@soton.ac.uk
Small area estimates of poverty and vulnerability to climate change in the Brahmaputra River Basin
Fiifi Amoako Johnson, Craig Hutton, Zoë Matthews
University of Southampton
The IPCC (1998) projections shows that climate change induced effects such as floods and droughts will impact greatly on the socio-economic wellbeing of individuals, households and communities. These changes are anticipated to impact on livelihoods, settlements, health, demographics and the environment including energy and water sources, sanitation, industry and infrastructure. The effects are hypothesized to vary greatly and felt more among poor and vulnerable communities due to limited resources and infrastructure. The Brahmaputra River Basin is one area where climate change induced effects are imminent. Adaptation strategies necessary to counter climate change induced effects are well documented in the literature. However, statistics to evaluate and monitor the vulnerability and adaptive capacity of at risk populations is almost non-existent particularly in developing countries. Census from which such statistics could be derived are limited in the amount of information they collect and are also becoming less regular in most countries due the high cost involved. Surveys which collect such information and are conducted on a more regular basis cannot be used to derive reliable sub-national estimates due to small samples from such areas. In this study we combine survey, census information and administrative data and using model-based small area estimation techniques derive local level estimates of socio-economic indicators required to evaluate and monitor the vulnerability and adaptive capacity of at risk populations in the Brahmaputra River Basin of Assam in India, Tibet in China and Bhutan.
Email: faj100@soton.ac.uk
Who is to blame? The role of family, community and state in determining school enrolment in Tajikistan.
Angela Baschieri1 and Jane Falkingham2
1Southampton Statistical Sciences Research Institute (S3RI), University of Southampton
2 Division of Social Statistics, School of Social Sciences, University of Southampton
This paper examines the factors associated with school role amongst children aged 7-17 in Tajikistan. It is hypothesized that after controlling for household characteristics enrolment rates, particularly amongst older children, will be lower in areas where the opportunity cost of education is higher, for example where there are more opportunities for cash labour or where travel costs are high. The paper uses household and community data from the 2003 Tajikistan Living Standards Measurement Survey combined with aggregate data at the PSU level from the 2000 Census as well as spatial data from remote sensoring on land use. Logistic multi-level modeling is applied to investigate the spatial variability of enrolment and to examine the relative role of variables at the individual, family and community level. It is found that enrolment varies according to availability of secondary school within the community, community perceptions of the quality of schooling offered and the percentage of land with a slope below 5 degrees.
Emails: ab5@socsci.soton.ac.uk & jcf1@socsci.soton.ac.uk
Wendy Pontin
Norfolk County Council
Norfolk is a large rural county having a wide range of both urban and rural LEA schools of varying type and size. There is a requirement for both catchment based residence pupil forecasts as well as forecasts of numbers of pupils on school rolls.
A pilot has been undertaken to test a new improved model that forecasts, by year group
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numbers of children resident in defined school catchments, taking account of predicted new house build and
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numbers of children on school rolls according to predicted patterns of parental preference and taking account of school capacity
The methodology relies heavily on the aggregation in GIS of all school pupils and 0 to 4 year olds, geo-referenced by their postcode of residence. Historical records are analysed to build trended residence based cohort survival rates and from current pupil records patterns of parental preference are constructed. The model itself has been developed as a set of interactive EXCEL spreadsheets.
This paper will give an overview of the methodology adopted, some initial results and discuss the pitfalls, problems and successes encountered during the pilot study.
Email: wendy.pontin@norfolk.gov.uk