Major demographic changes in Bangladesh and their socio-economic correlates: Analysis of trends

Catalogues the demographic changes in Bangladesh during the period 1975-2000 and examines how they relate to key socio-economic attributes. Trends are examined in population growth, growth of the working age population, women’s workforce participation, age-dependency ratio, female-male ratio, longevity, fertility, mortality and mean age at first marriage. Bangladesh has made significant breakthroughs in all these areas, a feat not matched by most other South Asian countries, but comparable with the South-East Asia region as whole. The study isolates factors contributing to the changes in each attribute. It assesses the correlation between Bangladesh’s demographic changes and selected socio-economic indicators namely, its per capita GDP, female labour force participation, per capita public health expenditure and educational achievements by both men and women. All five socio-economic variables display statistically significant correlation, in varying degrees, with measures of the demographic changes. Per capita GDP is probably the most significant determinant of demographic changes in Bangladesh. The study observes that men’s education reinforces women’s education and with increased workforce participation contributed to reduced fertility. The study suggests that the role of family planning programs in curbing population growth in Bangladesh maybe overestimated.

Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

Analyzing the researcher's work in generating data: The case of complaints

This article investigates the researcher's work in the coproduction (or not) of complaint sequences in research interviews. Using a conversation analytic approach, we show how the interviewer's management of complaint sequences in a research setting is consequential for subsequent talk and thus directly affects the data generated. In the examples shown here, researchers sharing cocategorial incumbency with respondents may well provide spaces for research participants to formulate complaints. This article examines sequences of talk surrounding complaints to show how researchers generate complaints (or not) and handle unsafe complaints. Researchers are able to provoke specific types of accounts from respondents, whereas their respondents may actively resist the researchers' direction. For researchers using the interview as a method of data generation, examination of complaint sequences and how these appear in interview data provides insight into how interview talk is coproduced and managed within a socially situated setting.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

Determinants of hepato- and spleno-megaly in Hunan, China: cross-sectional survey data from areas endemic for schistosomiasis

In order to understand the determinants of schistosome-related hepato- and spleno-megaly better, 14 002 subjects aged 3-60 years (59% male; mean age =32 years) were randomly selected from 43 villages, all in Hunan province, China, where schistosomiasis caused by Schistosoma japonicum is endemic. The abdomen of each subject was examined along the mid-sternal (MSL) and mid-clavicular lines, for evidence of current hepato- and/or spleno-megaly, and a questionnaire was used to collect information on the medical history of each individual. Current infections with S. japonicum were detected by stool examination. Almost all (99.8%) of the subjects were ethnically Han by descent and most (77%) were engaged in farming. Although schistosomiasis appeared common (42% of the subjects claiming to have had the disease), only 45% of the subjects said they had received anti-schistosomiasis drugs. Overall, 1982 (14%) of the subjects had S. japonicum infections (as revealed by miracidium-hatching tests and/or Katon Katz smears) when examined and 22% had palpable hepatomegaly (i.e. enlargement of at least 3 cm along the MSL), although only 2.5% had any form of detectable splenomegaly (i.e. a Hackett's grade of at least 1). Multiple logistic regression revealed that male subjects, fishermen, farmers, subjects aged greater than or equal to 25 years, subjects with a history of schistosomiasis, and subjects who had had bloody stools in the previous 2 weeks were all at relatively high risk of hepato- and/or spleno-megaly. In areas moderately endemic for Schistosoma japonicum, occupational exposure and disease history appear to be good predictors of current disease status among older residents. These results reconfirm those reported earlier in the same region.